Download - Semiconductor Industry Primer

Please see page 111 for rating definitions, important disclosures and required analyst certifications All estimates/forecasts are as of 11/14/14 unless otherwise stated.

Wells Fargo Securities, LLC does and seeks to do business with companies covered in its research reports. As a result, investors should be aware that the firm may have a conflict of interest that could affect the objectivity of the report and investors should consider this report as only a single factor in making their investment decision.

SEMIDUC111314-153101

November 14, 2014

Equity Research

Semiconductor Industry Primer 2014

Semiconductors

David Wong, CFA, PhD, Senior Analyst(212) 214-5007

[email protected] Chanda, Associate Analyst

(314) [email protected]

Parker Paulin, Associate Analyst(212) 214-5066

[email protected] E. Long, Associate Analyst

(212) 214-8017charles.e. [email protected]

Source for cover image of Intel Broadwell wafer: Intel (copyright Intel, reproduced with permission)

WELLS FARGO SECURITIES, LLC Semiconductor Industry Primer 2014 EQUITY RESEARCH DEPARTMENT

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TABLE OF CONTENTS

Map Of The Semiconductor Industry .............................................................................................................................................................. 5

Semiconductor Companies ....................................................................................................................................................................... 5

Types Of Semiconductors ......................................................................................................................................................................... 6

Semiconductor End Markets .................................................................................................................................................................... 7

Semiconductor Industry Dynamics ................................................................................................................................................................ 8

Growth ...................................................................................................................................................................................................... 8

The Semiconductor Cycle ....................................................................................................................................................................... 11

Pricing ..................................................................................................................................................................................................... 14

Capacity And Capacity Investment ........................................................................................................................................................ 17

The Rise Of The Foundries .................................................................................................................................................................... 24

Semiconductor Inventory And The Electronics Supply Chain ............................................................................................................ 29

Semiconductor Segments............................................................................................................................................................................... 35

Analog .................................................................................................................................................................................................... 38

Logic ....................................................................................................................................................................................................... 39

Memory ................................................................................................................................................................................................... 41

Discrete Components ............................................................................................................................................................................ 42

Sub-Segments Of Interest ..................................................................................................................................................................... 46

Microprocessor Technology Topics ................................................................................................................................................ 54

Applications Processors .................................................................................................................................................................. 56

Discrete Graphics ........................................................................................................................................................................... 63

Memory ............................................................................................................................................................................................ 65

Analog .............................................................................................................................................................................................. 81

PLDs ................................................................................................................................................................................................ 85

Selected Technology Topics ........................................................................................................................................................................... 91

Semiconductor Wafers And Chips ......................................................................................................................................................... 91

Manufacturing Transitions -- Line Widths And Wafer Size ................................................................................................................ 92

Calculating The Number of Circuits Of A Wafer (Die Per Wafer) ....................................................................................................... 96

Transistors -- What They Are And Some Technical Terms ................................................................................................................... 97

Lithography -- Multi-patterning And EUV ......................................................................................................................................... 100

Appendix A: Semiconductor Companies ..................................................................................................................................................... 102

Appendix B: Glossary ................................................................................................................................................................................... 105

WELLS FARGO SECURITIES, LLC Semiconductors EQUITY RESEARCH DEPARTMENT

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Map Of The Semiconductor Industry

Semiconductor Companies

Worldwide semiconductor sales amounted to $315 billion in 2013, up from $300 billion in 2012. Exhibit 1 lists the world’s largest semiconductor companies by 2013 revenue share.

Exhibit 1. The World’s Largest Semiconductor Companies By Revenue Share (2013)

Intel, 15%

Samsung Electronics, 10%

Qualcomm, 5%

SK Hynix, 4%

Micron Technology, 4%

Toshiba, 4%

Texas Instruments, 3%

Broadcom, 3%

STMicroelectronics, 3%

Renesas Electronics, 3%

Others, 35%

Companies with shares between 1%

and 2%, AMD, Infineon, SanDisk,

NXP, MediaTek, Freescale, Sony,

Marvell, Nvidia, 12%

Note: Chart created by Wells Fargo Securities, LLC (based on Gartner data) Source: Gartner, Inc., Market Share: Semiconductor Applications, Worldwide, 2013, Gerald Van Hoy et alia, March 31, 2014 The semiconductor industry as a whole is somewhat fragmented. The top nine companies make up more than half of total semiconductor sales, but the remaining half of the market is served by a large number of companies, each with market share of 2% or less. However, the industry contains several quite distinct segments, of which many semiconductor companies focus on just one or two. As a result, there are a number of major segments and sub-segments in which there are just two or three primary competitors. We discuss this in more detail further on in this report.

Intel is the largest semiconductor company, accounting for about 15% of total semiconductor sales. The bulk of Intel’s business is related to the computer end market. Intel is the market leader in microprocessors, the chips that act as the brains of the computers.

Samsung is the second-largest semiconductor company, with about 10% of total semiconductor industry sales in 2013. Semiconductors are just 16% of Samsung’s total sales. Samsung is also a major producer of wireless handsets and flat panel displays. Samsung is the world’s largest semiconductor memory company. Samsung’s Memory subgroup, which includes mainly dynamic random access memory (DRAM) and NAND flash memory, accounts for 60-70% of Samsung’s semiconductor revenue, with the rest of Samsung’s semiconductor revenue coming from a variety of logic and other chips from Samsung’s LSI group. Samsung’s semiconductor division also offers foundry services in which it manufactures chips for other companies. Apple currently uses Samsung and TSMC as foundry partners for the processors it uses in its iPhone and iPad products.

Qualcomm, a producer of semiconductor chips for wireless handsets, is the world’s largest fabless company. A fabless company is a company that does not own its own manufacturing facilities, i.e., fabrication facilities (or fabs). Qualcomm’s main chip business is designing and selling communications chips and processors for smartphones. In addition to selling chips for wireless handsets and other mobile


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devices such as tablets, Qualcomm also derives about one-third of its total revenue and about two-thirds of its profit from royalties paid by wireless handset makers.

Texas Instruments, often referred to as TI, is the world’s largest analog semiconductor company. Analog chips are chips that deal with continuous electrical signals or with electrical power, rather than digital signals (i.e., signals that represent either a 1, or a 0). Digital chips are used in the heart of many modern electronics to do calculations. Analog chips are the interface between the real world and the digital heart of an electronics system. About 60% of TI’s revenue is from its analog division, and an additional 20% is from TI’s embedded processing division, which TI considers to be complementary to analog. TI’s embedded processing products include microcontrollers (small thinking chips) and digital signal processors (thinking chips that are optimized to do the calculations related to analyzing electrical signals).

Types Of Semiconductors Exhibit 2. Types Of Semiconductors (2013)

Discretes, 6% Optoelectronics & Sensors, 12%

IC, 82%

Source: Semiconductor Industry Association and Wells Fargo Securities, LLC Semiconductors can be divided into three broad categories (see Exhibit 2):

Integrated circuits (ICs). ICs are semiconductor devices (chips) on which an entire electrical circuit is created. More than 80% of all semiconductor sales are of integrated circuits. ICs are used for most electronics applications in which semiconductors are needed. The price of an integrated circuit can range from tens of cents to several thousand dollars, with the average price of an integrated circuit currently running at about $1.20-1.30. Microprocessors are one category of IC that are quite expensive, with Intel’s average microprocessor price being more than $100 and the price of Intel’s more expensive server chips stretching above $1,000. Memory chips typically have a price of a dollar to a few dollars. Analog chips, while generally being highly profitable, tend to have low average selling prices (ASP), of the order of $0.30-0.50. Most of our discussion in this report is centered on ICs since they account for the bulk of the industry, and most of the major semiconductor companies are primarily IC companies.

Discrete semiconductors. Discrete semiconductors are single semiconductor devices (as opposed to integrated circuits, which are made up of several devices all connected together on the same chip). Discretes are used in many electronic applications, but one important use of discrete devices is in managing electric power. Prices for discrete semiconductor devices range typically from a few cents to a dollar or more, with the average price for a discrete being about $0.05. Discretes account for approximately 6% of total semiconductor sales. Discrete semiconductors have been slowly declining as a percent of total semiconductor sales over the years, in part, we think, because integrated circuits have been incorporating some of the functionality of discrete devices.


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Optoelectronics and sensors. Semiconductors that can be used to generate light (e.g., for displays, for traffic lights, to drive communications signals along optical fibers) or sense light (e.g., in digital cameras) fall into the category of optoelectronics. Generally the technology used to make optoelectronic devices is different from that needed to make integrated circuits or what we have defined as discrete semiconductor devices, and so there is, for the most part, a different set of companies that participates in this segment. Sensors are used to sense temperature, pressure, acceleration (e.g., to activate the airbag in a car), and other things. As with optoelectronics, this is a fairly small segment of semiconductors. A number of analog IC companies have become interested in sensor technology since the output of sensors is typically handled by analog chips. Solar cells are a potentially huge application for semiconductors, but are generally considered a different market from optoelectronics and sensors. The revenue number we have used to calculate the 12% of semiconductors does not include solar cell revenue, even though from an engineering point of view solar cells are, in fact, optoelectronic devices. We do not discuss optoelectronics, sensors, or solar cells further in this report.

Semiconductor End Markets

Exhibit 3 shows semiconductor sales by end market.

Exhibit 3. Semiconductor End Markets (2013)

Automotive, 8%

Consumer, 12%Wired Communications,

6%

Wireless Communications,

24%

Data Processing Compute+Storage,

39%

Industrial/Medical/Other, 9%

Military/Aerospace, 1%

Note: Chart created by Wells Fargo Securities, LLC (based on Gartner data) Source: Gartner, Inc., Market Share: Semiconductor Applications, Worldwide, 2013, Gerald Van Hoy et alia, March 31, 2014

Gartner estimates that computing (data processing--compute plus storage) accounts for roughly 39% of total semiconductor sales. Computing tends to require leading-edge semiconductor technology, especially in microprocessors and memory (DRAM). Nearly 300 million personal computers (PCs) shipped worldwide in 2013, and about 200 million tablets, we estimate. Server systems, while having lower volume (on the order of 10 million server systems shipped worldwide in 2013) have very high semiconductor content, including many chips with high prices and high gross margin. For example, Intel’s Data Center Group (chips for servers and other computer infrastructure systems) contributes about a quarter of Intel’s total revenue and nearly a third of Intel’s operating profit. Tablets and convertible devices continue to grow as a source of semiconductor demand. In 2013, Wireless communications (mostly wireless handsets) accounted for 24% of semiconductor consumption and are a high-volume segment, as about 1.8 billion wireless handsets were shipped worldwide in 2013 (up 4% yr/yr). We think that as handsets become more sophisticated with the rise of smartphones, there may be good opportunities for increasing semiconductor content per handset. However, we view the overall handset market as being somewhat saturated, with a worldwide installed base of perhaps close to 4.6 billion handsets.


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Consumer electronics accounted for 12% of total semiconductor consumption in 2013. This segment contains a broad range of product such as camcorders, set top boxes, DVD players, TV, cameras, and video game consoles. We view this as one of the slower growing segments of all the semiconductor end markets. As new consumer devices crop up, older products fade.

Increasing semiconductor content is a driver for semiconductor growth in the automotive end market (about 8% of semiconductor consumption). Semiconductor applications in cars include sensors (e.g., every airbag has a micromechanical semiconductor sensor that triggers when rapid deceleration occurs during a crash), microcontrollers (e.g., antilock brakes), wireless (e.g., the signal that tells the car to lock its doors), electronic power (e.g., the drivers that lock and unlock the doors), and displays (e.g., dashboard lighting). We believe the growing popularity of on-board navigation systems and TV/DVD systems will provide ongoing momentum for increasing content in automobiles. Electric cars also have substantial semiconductor content associated with the handling of the electric power.

Semiconductor Industry Dynamics

Growth

Exhibit 4 details total worldwide semiconductor sales in dollar terms on a log scale in order to show the long-term growth trend. Exhibit 5 shows semiconductor data on a linear scale. Exhibit 4. Worldwide Semiconductor Sales With Growth Trends

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vera

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ents

$00

0s

Monthly Sales 12/85-12/00 15%/yr

Source: Semiconductor Industry Association, Wells Fargo Securities, LLC

Semiconductor sales grew at a rate of about 15% per year from 1985 to 2000. Although there is, we think, a widely held belief that there was excessive buying of technology-related goods in 1999 and 2000, the graph does not show semiconductor sales much above the longer term trend line in 1999 or 2000. From 2001 through today (2014), revenue growth for the semiconductor industry has been far lower, following a trend of about 4% per year growth. As we discuss below, we believe that the true underlying long-term sales growth rate for semiconductors may be between these two numbers, of the order of about 10% per year.


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Exhibit 5. Total Worldwide Semiconductor Sales (Three-Month Rolling Average)

- 2,000,000 4,000,000 6,000,000 8,000,000

10,000,000 12,000,000 14,000,000 16,000,000 18,000,000 20,000,000 22,000,000 24,000,000 26,000,000 28,000,000 30,000,000 32,000,000

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Mth

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vg.

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000s

Worldwide Chip Sales

Source: Semiconductor Industry Association and Wells Fargo Securities, LLC

Exhibit 5 shows:

Semiconductor sales recovered steadily from 2002 through 2006 following the downturn of 2000-01, with sales reaching year-2000 highs in H2 2004.

The years 2007 and 2008 were ones of modest growth for semiconductors.

Semiconductor demand dropped sharply at the end of 2008 and early 2009 with the global macroeconomic issues that emerged during this period.

The industry recovered as 2009 progressed and managed to end 2010 with record volume.

Global semiconductor sales were flat year over year in 2011 and down 3% in 2012, even though the global economy grew 4% in 2011 and 3% in 2012.

Semiconductor sales rebounded in 2013, growing 5% year over year, compared to global growth of about 3%. However, the growth in 2013 was largely a reversal of the decline in 2012.

As electronics continue to penetrate further into essentially every aspect of human activity, we think it is likely that semiconductor growth will in general pace above global GDP growth. From 2011 through 2013, semiconductor industry growth in total for the three years was 2%, far below the 10% total expansion of global GDP. We think this may indicate that there is some pent-up demand for a range of electronics goods that could be realized as the global economy continues to recover. For the period January-September 2014 (the most recent data available at the time of writing this report), global semiconductor sales rose 10% year over year.

Exhibit 6 shows that an interesting picture emerges when we look at unit shipments, as opposed to sales in dollars. In discussing unit trends, we look at integrated circuit (IC) unit numbers, rather that total semiconductor unit numbers since otherwise the very low-priced discrete chips would distort the trends. Discrete semiconductors have an average selling price (ASP) of about $0.05, versus the IC ASP, which is currently close to $1.30. Therefore, discrete semiconductors account for a far larger percentage of unit shipments than their proportion of economic value to the semiconductor industry.


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Exhibit 6. Worldwide Integrated Circuit (IC) Unit Shipments

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100,000,000

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IC M

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IC Monthly Unit Ships 1/85-12/00 10%/yr


IC unit shipment growth of 10% per year from 1985 to 2000 was 6 percentage points less than sales growth in dollar terms, which implies pricing expansion during this period.

In contrast to semiconductor sales in dollar terms, while unit shipments did drop sharply in 2001, the recovery from 2002 to 2007 pulled unit shipment levels back to the longer term trend line extrapolated from 1985 to 2000. Following the economic downturn of 2008/2009, unit shipments move back up in 2010 to the long-term trend line we have shown in our graph. Hence, for the 25-year period from 1985 through 2010, there was been a consistent trend of solid unit growth of 10% per year for semiconductor units. Admittedly, the unit numbers have dropped below our trend line in the past 3-4 years, though, as discussed above, we believe that this is a sign that some amount of pent-up demand has been created, rather than it being a reflection of the underlying trend of global chip growth suddenly slowing after 2010.

The discrepancy between sales growth and unit growth from 2000 to 2010 was the result of falling ASPs. As we discuss further on, IC ASP today is close to where it was in 1990. The decline from 2000 to 2010 roughly matched the expansion from 1990 to 2000. The 20+ year trend does not show any obvious ASP decline.

We conclude that there is good reason to expect that the semiconductor industry should continue to achieve IC unit growth of 10% per year, with potentially some amount of “catch up” in the near term from the softness of 2011-13. We expect this unit growth to be driven by a combination of solid unit growth in the major semiconductor end markets, as well as increasing semiconductor content in a number of key markets such as wireless handsets and automotive electronics. As discussed below, we think that over the next few years, IC ASP could well be flat to up, which, combined with unit growth of 10% per year or better, could result in overall semiconductor industry sales growth in the 10-12% per year range over the next several years.


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Seasonality

In the past, PC sales showed a clear seasonal pattern, with H2 of each year typically being significantly stronger than H1. March quarter shipments are often down sharply from those of the preceding December quarter. For semiconductors as a whole, June quarter shipments tend to be slightly up from March quarter shipment levels, though in some segments such as for, example, PC-related chips, June sales can be flat to down from March. September quarter sales are usually up sharply from June quarter sales, and there is often another increase in sales from the September quarter to the December quarter, driven by the seasonal pattern for electronics products such as consumer PCs, wireless handsets, and other consumer electronics. Since chip purchases and system builds occur before the systems are sold, though some chip companies see demand peaking at some point in the September-November time frame, and so some chip companies typically see muted sequential growth or even slight sequential declines in the December quarter.

The seasonality of wireless handset sales is similar to that of PCs, with some minor differences. The June quarter is typically stronger than the March quarter (whereas for PCs, the June quarter is similar to or weaker than the March quarter in most years). As with PCs, the September quarter is stronger than the June quarter for wireless handsets, the December quarter is stronger than the September quarter, and the March quarter is down from the preceding December quarter. The monthly global semiconductor shipment data released by the Semiconductor Industry Association (SIA) typically shows a month-over-month decline in the month of December.

The market for communications infrastructure chips often shows softness in the September quarter, with September sales being flat or down sequentially compared to June. This is to some extent associated with a drop in demand in Europe, perhaps associated in part with summer vacations in Europe.

Some segments of the industrial end markets show strength in the beginning of the year, with the March quarter being up sequentially over the December quarter.

There is a delay between the purchase of semiconductor components and the sale of the systems (such as PCs and wireless handsets) in which the semiconductors are used. We assume that the offset between semiconductor sales and systems sales is in aggregate about 1-2 months. This results in slight differences between semiconductor seasonality and end-market seasonality.

The Semiconductor Cycle

In the past, the semiconductor cycle has been supply driven, not demand driven (see Exhibit 7). On the supply side, we believe the capital-intensive nature of semiconductor manufacturing and the time lag between investing in new capacity and actually being able to use the new capacity is responsible for this pattern:

A new state-of-the-art fab can cost $6 billion or more to construct and equip today.

The building construction for a new fab might take six months to a year. Moving in the manufacturing equipment and getting it ready to process semiconductors (i.e., qualification of the equipment) takes several additional months.

On the demand side, in our view, the major semiconductor end markets have not shown any obvious cyclical behavior, apart from seasonal patterns over the course of each year and swings associated with macroeconomic downturns and recoveries.

In theory, when capacity is tight, semiconductor pricing should rise causing an acceleration of semiconductor growth in dollar terms. Tight capacity also causes end customers and distributors to increase days of semiconductor inventory held. It takes time to make the decision to invest in more capacity and then to bring that capacity online. When the additional capacity comes online (and in particular, if excess capacity is created), pricing moderates, growth decelerates, and end customers decrease days of semiconductor inventory held.


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Exhibit 7. The Semiconductor Cycle--(Year-Over-Year Growth Of IC Sales And Units)

(60%)

(40%)

(20%)

0%

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80%D

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Yr/

Yr

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wth

Yr/Yr chg IC sales Yr/Yr chg IC units

Source: Semiconductor Industry Association and Wells Fargo Securities, LLC estimates

Exhibit 7 shows the semiconductor cycle. The solid line represents yr/yr sales growth in dollars and the crosses show yr/yr unit growth.

The period from 1985 to 1999 shows two complete cycles. The cycle shows up in the yr/yr growth in dollars. Although unit growth does fluctuate, it does not show the same clear cyclical behavior as sales growth in dollars.

We believe that the period from 2000 to mid-2003 is unusual and not part of the cyclical pattern because of the impact of unusual softness in worldwide economies.

In the 1985-1999 period, the length of a full cycle was about seven years. This was made up of about 3.5 years of strong growth in dollar sales ranging from 20% to 40% per year, and about 3.5 years of weaker growth (or even declines) in the negative 20% to positive 20% range.

The cycle is driven by dollars sales growth being higher than unit shipment growth (the continuous line is, for the most part, above the crosses in the graph). This implies pricing expansion. In the negative phase of the cycle, from 1989 to 1991, sales growth was comparable with unit shipment growth; pricing had a neutral impact. On the other hand, in the downturn from 1995 to 1998, dollars sales growth was lower than unit shipment growth (continuous line below the crosses), implying a decline in pricing.

We interpret unit shipment growth as an indicator of overall demand. Unit shipment growth, and by implication, demand, does not show any obvious cyclical behavior. This is consistent with the absence of cyclical behavior in PC shipments and any of the other major semiconductor end markets.

In the past, the cyclical pattern for semiconductors was driven by pricing. Given no clear cyclical pattern in demand, we conclude that semiconductor pricing patterns are far more a function of availability of supply (capacity utilization) than a result of fluctuating demand. In the next subsection we discuss pricing and in the following subsection we look at capacity.

In H2 2003 it began to look (at the time) as if the industry was returning to normal cyclical behavior. Units had been growing steadily in a more or less normal seasonal pattern since early 2002 and in H2 2003, yr/yr sales growth in dollars overtook unit growth; pricing was expanding. We had expected the industry to go into a three and a half-year expansion phase, driven by pricing expansion. However, in H2 2004, semiconductor unit growth started to decline on a month-over-month basis, the result of an inventory correction stemming from too much chip buying in H1 2004. A “mid-cycle correction” in the yr/yr growth pattern for unit shipments is not unusual; it can be seen that there was a dip in unit growth in early 1987 and in 1994, in the middle of the high-growth phases of the previous two cycles. What was unusual this time, though, was the crossover of sales


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growth and unit growth following this correction. Pricing declined and yr/yr pricing comparisons turned negative around mid-2005 and remained negative in the next three years through 2008.

Then, in H2 2008, the global economic downturn drove down semiconductor unit demand sharply. This was not a semiconductor-specific event but instead, a broader issue affecting all segments of the economy. Growth picked up sharply in H2 2009 before returning to more normal levels in 2010. So far in 2014, growth has been moderate, below the 10% growth trend.

The trends of the past 12 years raise the question as to whether there has been any change in the cyclical behavior of the semiconductor industry. Some things have not changed:

Semiconductor manufacturing remains capital-intensive, although the transition to 300mm has resulted in a small step down in investment percent over the past few years.

As an example of the costs associated with these new facilities, Intel’s Fab 42 (for 14nm chips on 300mm wafers) is expected to cost more than $5 billion to construct. In addition, with the move to ever larger wafer sizes, the minimum reasonable size of a fab has soared 10-100x over the past 15 years.

Capacity in general has to be brought on in fairly large chunks, especially when a new facility has to be constructed. Despite this, it still takes a fair amount of time to actually bring up new capacity. It can take 1-2 years to build, equip, and bring up a fab from scratch. Just to expand production in an existing facility by moving in more production equipment typically takes a minimum of six months or so.

However, some things have changed, and those changes could reasonably be expected to dampen (improve) the cyclical behavior of the semiconductor industry in the future:

More and more semiconductor companies are fabless, having their manufacturing done by third parties, that is, the semiconductor foundries. This decouples the capital intensity from the companies selling the chips. Tightness in capacity leading to chip shortages is still a mechanism that can drive pricing upward. However, the fabless chip companies are buffered from problems of excess capacity. It is someone else’s problem. Therefore, excess capacity at the foundries does not immediately lead to a collapse of chip pricing in an effort by the owners of the capacity to fill up their excess capacity.

It appears that in recent years, semiconductor manufacturers have become far more profit-conscious and cautious about the risk of creating excess capacity. In the decade of the 1990s, we believe the top priority at many major semiconductor companies was to drive sales growth. We believe that in recent years there has been far more focus among chip company management teams on improving profit margin. This change in priority in the industry has led to a lot more focus on capital efficiency and a more rapid response to cutting back on capital spending when business conditions have weakened.

The capacity/pricing sensitivity is strongest in commodity-like semiconductors, of which memory is one of the largest segments. Most of the big memory makers still run their own fabs, rather than using foundries (in part because in a commodity-like business with thin profit margin, it does not make financial sense to share that margin with a third-party manufacturer), and it seems likely that this will remain true indefinitely. However, in recent years, two major semiconductor memory manufacturers, including Qimonda (owned by Infineon) and Elpida have declared bankruptcy. Micron’s acquisition of Elpida closed last year (2013). We think that the reduction in the number of memory competitors may well result in more stability in memory pricing in the future.

Our graph shows that since the year 2000, there has been no multiyear sustained period in which pricing expansion (sales growth tracking above unit growth) has driven the upward leg of a semiconductor-specific cycle. It appears as if the cyclical component of the semiconductor industry has disappeared, with no obvious sign of a semiconductor specific cycle (apart from economic cycles that have affected all industry) over the past 14 years. We believe that there will be more consistent growth and less cyclical behavior in the semiconductor industry in the future than there was in the past. This is a positive development, in our view, as it should allow semiconductor companies to be more efficient in their use of capital and make it easier to plan for growth.


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Pricing

Exhibit 8 shows ICs currently have an ASP of around $1.25, while discrete semiconductors are much less expensive, with an average price of about $0.05. Prices for individual ICs range from tens of cents to hundreds of dollars. Prices for discrete semiconductor products range from cents to tens of cents.

Exhibit 8. Total Integrated Circuit Average Selling Price

$0.00

$0.50

$1.00

$1.50

$2.00

$2.50

$3.00

$3.50

To

tal

IC A

ve.

Pri

ce


The very big discrepancy between discrete and IC ASP means that discretes have a far bigger impact on overall semiconductor unit shipments than their true economic value warrants. This is why we normally analyze and discuss IC unit shipment trends rather than total semiconductor shipment trends (although the two do tend to track). Even within ICs there is a broad range of prices and therefore, commentary on even IC unit shipments can sometimes be misleading. With IC ASPs currently a little above $1, Intel’s desktop and notebook microprocessors have an average selling price of about $130. Therefore, Intel, the world’s largest semiconductor company, has a disproportionately small impact on worldwide semiconductor unit shipments than some other companies that are far smaller than Intel in terms of total sales.

Blended IC ASPs:

Were relatively constant from 1979 to 1987, at close to $1.00;

Rose from 1987 to 1990;

Soared from 1990 to 1995, to as high as about $3.00, driven by high dynamic random access memory (DRAM) prices;

Dropped from 1995 to 1997 (DRAM price correction), but then rose again from 1997 to 2000, to close to $2.00;

Corrected from 2000 to 2001, to about $1.50;

Were fairly constant from 2001 to 2003;

Rose in 2004, only to fall back in 2005 and drift down from 2005 through 2008.

From 2008 through the present (late 2014), IC ASPs have remained fairly stable, running in the $1.20-1.50 range.


15

Some factors that have affected semiconductor ASP at various points in the past include memory price changes, a dip in semiconductor demand, and the rise of microprocessors.

Memory prices drove ASP up from 1990 to 1995. DRAM had an anomalous period from 1991 to 1995, in which prices deviated from the long-term trend, in the positive direction. Our numbers show that from 1990 to 1995, DRAM ASP rose to nearly $9 from below $4. Jumping forward to Exhibit 50, it can be seen that price per bit (discussed in some detail further on) for DRAM has generally followed a decline of 35% per year, but price per bit remained flat from 1991 to 1995. This helped drive overall IC ASPs upward from 1991 to 1995 (high growth in memory bits shipped with no price-per-bit decline). When memory prices suddenly corrected back to the longer term trend (a 35% per year price-per-bit decline), this led to a sharp IC ASP decline from 1995 to 1997. By 1999, memory ASP was back to about $3.50, close to where it had been in 1990. The spike in IC ASPs from 1990 to 1995 can largely be explained (as far as memory played a role) as a memory pricing, rather than a memory mix, effect.

Increasing microprocessor mix drove ASP up from 1990 to 2000. Although memory pricing had a huge positive impact on IC ASPs in the first half of the 1990s, the effect was reversed in the second half and so, over the course of the whole decade, pricing for memory was neutral to IC ASPs. The one thing we can identify that had a clear and permanent impact on driving up IC ASPs from 1990 to 2000 is microprocessors. From 1990 to 2000, the rise of the PC led to the emergence of microprocessors as a major semiconductor category. Microprocessors have much higher prices than most other chips, on the order of $40.00-120.00 today ($200+ in the 1990-2000 time frame) for high-volume desktop and notebook microprocessors. This had a positive influence on IC ASPs from 1990 to 2000. Microprocessors are just one sub-segment of overall logic and PC-microprocessors are a sub-segment of what the Semiconductor Industry Association (SIA) classifies as microprocessors. From 1990 to 1999, logic ASPs rose to about $2.80 from $1.30. In Exhibit 9 it can be seen that logic did grow some as a percentage of the total IC dollar mix from 1990 to 2000, but really, the big change was in logic ASPs. Within logic, microprocessor ASPs soared, as triple-digit PC microprocessor prices grew to dominate the microprocessor category, driving up microprocessors (MPU) as a percentage of the total logic mix (see Exhibit 10). From all this we can see that although on the surface it appears that the contribution of logic to rising IC ASPs through the 1990s was a pricing effect, it was in reality a mix effect within logic. As high-priced microprocessors grew to represent a greater percent of the overall logic segment, they drastically increased the pricing impact that logic had on overall IC ASPs.

A sharp downturn (bursting of the tech bubble) hit pricing in 2001. In 2001, semiconductor demand plunged by more than 20% yr/yr, producing excess capacity, which then caused prices to decline (see Exhibit 11).

Rising handset mix diluted the positive effect of microprocessors from 2003 to 2008. Even though the semiconductor industry did benefit from the recovery of 2003-08, with the number of unit shipments rising in this period and capacity utilization running at a comfortable 85-95%, IC ASPs continued to trend downward slowly, to about $1.30 in 2008 from about $1.50 in 2001. We think that this trend was in part due to slight mix shifts. For example, wireless handsets were an important end market, driving chip growth from 2001 to 2008. There are some chips in handsets that sell for several dollars, though this is nothing like the PC-driven microprocessor dynamic of the 1990-2000 period, with microprocessors selling for several hundred dollars becoming a larger part of the mix. Exhibit 10 shows that microprocessor sales dropped as a percentage of total logic sales, to 28% by 2009 from 35% in 2001.


16

ASP stability from 2009 through 2013. The sharp downturn toward the end of 2008 did not have the same large negative impact on IC ASPs as the downturn of 2001 had. Blended IC ASP has been relatively stable over the past four years, despite rapidly recovering demand through 2009 and 2010, followed by the inventory correction in the second half of 2011 and broad-based economic softness in 2011 and 2012. We think this is probably a result of more focus on management of capacity and capacity investment in the semiconductor industry, and also, the increasing proportion of chips sold by fabless companies.

Over the next few years, we think that some important drivers for semiconductor growth include smartphones, tablets, and servers, all of which should help improve mix, leading to a blended IC ASP trend that we think could be flat to up for some extended period of time. On the other hand, further into the future, the proliferation of lower cost electronics for Internet-of-things applications could pressure blended IC ASP.

Smartphones continue to grow as a percent of wireless handsets overall. Gartner data suggest that in 2013, smartphones accounted for about 54% of total handsets shipped worldwide, up from 39% in 2012. Smartphones have an applications processor, while lower end wireless handsets do not. The memory content of a smartphone (especially NAND flash) is generally higher than in a standard wireless handset.

Tablets contain applications processors and flash memory chips, both of which typically have prices that are a fair amount above the IC average.

Servers have a particularly rich mix of chips. A high percentage of servers have two or more microprocessors, with ASPs in the $600+ area. Servers also tend to have a large amount of high-density DRAM.

Exhibit 9. IC Mix Shift 1990-2013 (Sales)

Logic, 57%Analog, 16%

Memory, 27%

2013

Analog, 17%

Logic, 55%

Memory, 28%

2000

Analog, 19%

Logic, 51%

Memory, 30%

1990

Source for all charts: Semiconductor Industry Association and Wells Fargo Securities, LLC


17

Exhibit 10. Logic Mix Shift 1990-2013 (Sales Dollars)

MPU, 11%

MCU, 19%

MPR, 14%

General MOS Logic, 39%

Other, 17%

1990 MPU, 36%MCU, 19%

MPR, 14%

General MOS Logic,

31%Other, 1%

1999MPU, 28%MCU, 10%

DSP, 2%

Gen. MOS Logic &c.,

59%

2013

Source for all charts: Semiconductor Industry Association and Wells Fargo Securities, LLC estimates

Capacity And Capacity Investment

Semiconductor manufacturers make semiconductor chips on wafers (see the section on selected technology topics, which follows, for a fuller explanation of this). Sometimes semiconductor production quantities are described in “wafer starts per week” and sometimes, in “wafer outs per week.” Wafer starts per week represent the number of semiconductor wafers that a manufacturer begins processing each week. Wafer outs per week represent the number of wafers that are completed each week (the number of wafers coming out of the wafer fabrication facility). It typically takes about 12-13 weeks from the beginning of the process to the end of the process and so, the difference between wafers starts per week and wafer outs per week is a timing difference of one quarter. For example, Micron, on its conference calls, often neglects to clarify whether it is referring to wafer starts or wafer outs. This is an important distinction when trying to calculate output in a given quarter since the difference between the two is about one full quarter. When looking at semiconductor capacity data, sometimes semiconductor makers also quote capacity in wafer starts per month rather than in wafer starts per week. For example, Micron generally describes its capacity in terms of wafers per week, whereas many other memory chip makers quote capacity in wafers per month. Often in press releases and on conference calls, companies neglect to clarify whether they are referring to “per week” or “per month” numbers.

When a manufacturer builds a new factory (called a fab, a contraction of the term fabrication facility), first the building is constructed. This can take several months. Then semiconductor equipment is moved in. This can take several more months. A company will sometimes build a manufacturing space (i.e., a clean room) that is a fair bit larger than it initially needs and may fill only part of the clean room with equipment. There is thus a difference between “floor capacity,” that is, the capacity the company would have if it filled up all its available clean room space with equipment, and “installed capacity,” which is the number of wafers the manufacturer could process if all the machinery it bought was running all the time. Generally, capacity utilization refers to the utilization of the installed capacity.


18

Exhibit 11. Worldwide Semiconductor Capacity (millions of square inches) And Capacity Utilization

-

500.0

1,000.0

1,500.0

2,000.0

2,500.0

3,000.0

0.0

20.0

40.0

60.0

80.0

100.0

120.0

Total Utilization (%) Leading Edge Utilization(%) Worldwide Fab Capacity (Millions of square inches)

Note: Chart created by Wells Fargo Securities, LLC (based on Gartner data) Gartner, Inc.: Forecast: Semiconductor Wafer Fab Capacity, Worldwide, 2Q14 Update, David Christensen et alia

Exhibit 11 shows worldwide semiconductor capacity and capacity utilization. We consider capacity utilization of 90% and higher to be a healthy level. The capacity data of Exhibit 11 are described in terms of millions of square inches. Since the transition to different wafer sizes often takes place over the span of years, at any given point in time the semiconductor industry as a whole is doing its manufacturing on more than one wafer size. Currently, most manufacturing is done on 200mm (8 inch) and 300mm (12 inch) wafers, but there still remains some manufacturing on 6-inch and even some 5-, 4-, and 3-inch wafer processing. To normalize all these different wafer sizes, capacity numbers (and other things associated with wafers, for example, prices charged per wafer by foundries) are often couched in “wafer equivalent” numbers. A 300mm wafer has 2.25x the area of a 200mm wafer, and hence, 2.25 more chips can be fabricated on such a wafer. Therefore, a 300mm wafer would count as 2.25 equivalent 200mm wafers when adding up wafer capacity.

The data in Exhibit 11 are an aggregate of utilization rates across the semiconductor industry. However, the sensitivity of pricing to capacity utilization is different for different segments of the industry. The most sensitive segment is the memory segment since memory is a price-elastic commodity. However, although it is possible to get qualitative commentary on capacity utilization from the memory makers and some analysts track fab capacity availability and expansion at memory makers, so many factors appear to play into memory pricing that we question how fruitful it is to try to quantitatively predict future memory prices from capacity analysis.

Low capacity utilization does often result in chip pricing pressure. Semiconductor ASPs fell from 1997 to 1998, as did capacity utilization, and the entire semiconductor industry was hit by a big downturn in 2001, which resulted in falling capacity utilization and falling pricing. However, in the most recent downturn toward the end of 2008, although memory prices plunged in H2 2008, prices of other chips remained fairly stable. Memory prices rebounded in 2009, even as capacity utilization hit a low in the March 2009 quarter. We think that this was partly the result of aggressive action taken by the various participants of the electronics supply chain to cut production and inventory. This was effective in preventing problems of excess inventory.


19

Exhibit 12. U.S. Semiconductor and Related Capacity Utilization

50%

55%

60%

65%

70%

75%

80%

85%

90%

95%

100%M

ar-9

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ep

-92

Mar

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Source: Federal Reserve--Industrial Production/Capacity Utilization Release and Wells Fargo Securities, LLC

The U.S. Federal Reserve releases, on a monthly basis, capacity utilization data for “semiconductor and other electronic component manufacturing” in the United States. We have plotted this information in Exhibit 12. The U.S. data are interesting because they are presented monthly rather than quarterly. They generally reflect similar trends with the Gartner numbers. However, a substantial amount of semiconductor manufacturing is done outside the United States. Also the U.S. data include many other types of manufacturing besides semiconductor wafers, such as printed circuit boards, capacitors and resistors, electronic coils and transformers, electronic connectors, and other electronic components.

Exhibit 13. Taiwanese Foundry Utilization Rates

0

1,000,000

2,000,000

3,000,000

4,000,000

5,000,000

6,000,000

7,000,000

0%

20%

40%

60%

80%

100%

120%

140%

Cap

acity (200mm

Eq

uiv W

frs/Qtr)

Qu

arte

rly

Cap

acit

y U

tili

zati

on

Rat

e (%

)

UMC Capacity Utilization TSMC Capacity Utilization TSMC+UMC Capacity

Source: Company reports and Wells Fargo Securities, LLC estimates


20

The Taiwanese semiconductor foundries, TSMC and UMC, release quarterly numbers from which their capacity utilization can be calculated. Capacity utilization for both companies is plotted in Exhibit 13. The Taiwanese foundries are the only major semiconductor companies of which we are aware that routinely report specific capacity utilization information when they release earnings. Foundry capacity utilization tends to show much larger swings than overall worldwide capacity utilization. This makes sense for two reasons:

Some chip companies do their own manufacturing, as well as use foundries for making similar chips. During downturns, companies that have a choice between manufacturing in their own facilities, versus using foundries inevitably opt to maximize the use of their own fabs.

Companies that do their own manufacturing, i.e., independent device manufacturers (IDM), tend to balance the risk of creating excess inventory against the costs of underused fabs. Fabless companies do not have to concern themselves with holding up utilization at their foundries, and therefore, would be expected to cut wafer orders more aggressively in downturns than IDMs.

Exhibit 14. Some Of The Semiconductor Industry’s Largest Capital Spenders Company 2006 2007 2008 2009 2010 2011 2012 2013 2014E 2015E Date1 Intel2 $5.80 $5.00 $5.20 $4.50 $5.20 $10.8 11.0 $10.7 $10.5-$11.5 Oct 14, 2014 Micron3 (Aug FYE) $1.60 $4.10 $2.90 $0.63 $0.95 $2.9 $1.9 $1.24 $2.8-$3.2 $3.6-$4.0 Aug 5, 2014 Samsung $6.60 $7.80 $6.90 $3.50 $11.0 $11.6 $13.4 ~$11.3 ~$13.8 Oct 30, 2014 TSMC $2.50 $2.60 $1.89 $2.67 $5.90 $7.3 $8.3 $9.7 ~$9.6 ~$10 Oct 16, 2014 UMC $1.00 $0.90 $0.35 $0.50 $1.80 $1.6 $2.0 $1.1 $1.3 Oct 29, 2014 Hynix $5.10 $1.90 ~$0.8 $3.00 $3.3 $3.7 ~$3.2 ~$3.8 Oct 23, 2014 Globalfoundries4 $5.4 $9-10 Oct 20, 2014 1 Date last affirmed 2Intel’s 2013 capital spending included about $1.3 billion for 450mm spending; we think this could be about the same for 2014.

3Increase in Micron’s spending in 2014 is driven in part by Micron’s acquisition of Elpida. 4Globalfoundries has indicated that it has $9-10B capital expenditure planned in 2014-15. Source: Company reports and Wells Fargo Securities, LLC One way to estimate future capacity increases is to look at the capital expenditure (capex) of the semiconductor manufacturing companies. Exhibit 14 lists some of the top semiconductor companies in capital spending planned for 2014/2015.

In recent years the larger chip manufacturers, Intel, Samsung, and TSMC, typically have run (semiconductor) capex in the $8-14 billion per year range.

TSMC began aggressively ramping up its capex in 2010 and has continued to drive up capex through 2013. In 2014 and 2015 it appears that TSMC’s capex might be plateauing at close to the 2013 level.

Although Intel has noted that difficulties with lithography (imaging) for the most advanced technologies may well result in a need for higher levels of capital spending in the near term. On the other hand, while Intel’s capital spending more than doubled in 2011 from 2010 levels, Intel has been tracking on a plateau of close to $11 billion in capital spending in each of the past four years, 2011-14.


21

Exhibit 15. Semiconductor Industry Capital Intensity (Worldwide Semiconductor Equipment Purchases divided by Worldwide Integrated Circuit Sales)

0%

5%

10%

15%

20%

25%

30%

35%D

ec-9

0

Dec

-91

Dec

-92

Dec

-93

Dec

-94

Dec

-95

Dec

-96

Dec

-97

Dec

-98

Dec

-99

Dec

-00

Dec

-01

Dec

-02

Dec

-03

Dec

-04

Dec

-05

Dec

-06

Dec

-07

Dec

-08

Dec

-09

Dec

-10

Dec

-11

Dec

-12

Dec

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emi E

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/(IC

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es)

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th R

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Source: Semiconductor Industry Association, SEMI, and Wells Fargo Securities, LLC estimates and calculations

A more specific indicator for how semiconductor capacity might change in the near future (and to get a feel as to whether capacity utilization will remain tight, driving up pricing) is the purchases of semiconductor equipment. Exhibit 15 shows worldwide semiconductor manufacturing equipment sales as a percent of worldwide IC sales (basically a measure of the rate of reinvestment). The IC manufacturers account for the bulk of semiconductor equipment purchases, which is why we use IC sales, rather than total semiconductor sales to normalize the semiconductor equipment numbers.

In principle, spending below the “equilibrium” ratio implies a reduction in capacity and potentially, higher capacity utilization, while spending above the equilibrium point implies an increase in capacity and potentially, a fall in capacity utilization (if the capacity is growing faster than demand. However, the equilibrium ratio has shifted over the years, driven by a number of major secular trends:

(1) The ratio of semiconductor equipment spending as a fraction of IC sales rose from 1990 to 2000. In fact, although we have not plotted data prior to 1990 on the graph (for lack of a consistent data set), the ratio of equipment spending to IC sales rose through the first three decades of the life of the semiconductor industry, from 1970 to 2000. Some of this was due to the fact that semiconductor equipment makers continually increased their contribution to the semiconductor manufacturing process. One example of this is automation. In the late 1980s, almost all operators had to manually load wafers onto machines, and wafers had to be carried from one machine to the other by operators. By the end of the 1990s, almost all semiconductor equipment had precision robotics that automatically loaded wafers into the machines, and some fabs had installed fab-wide automation, in which wafers could be mechanically moved from one machine to the next. Robotic handling is expensive. The price of some machines increased as much as tenfold, to millions of dollars from hundreds of thousands of dollars. This increased the capital intensity of the semiconductor business. The cost of constructing and equipping a semiconductor fab rose to hundreds of millions of dollars in the 1990s from tens of millions, to the current level of several billion dollars for a leading-edge semiconductor fab. However, it does not follow that the profitability dropped or that the absolute cost of making semiconductor chips rose through time. For example, automation results in higher semiconductor equipment cost, but reduced labor cost.


22

(2) An opposing trend that should in principle decrease the ratio of equipment purchases to chip sales is the increase in wafer size. Over time, semiconductor manufacturers have increased the size of the wafers used to make semiconductor chips. In the early 1990s, manufacturers were shifting to six-inch wafers (diameter) from five-inch. In the mid-1990s, the transition to eight-inch (200mm) wafers from six-inch wafers took place. Over the past few years, manufacturers have been moving to 300mm (12 inch) wafers from 200mm (8 inch) wafers. The increase in the cost of a machine that can deal with a larger wafer size is in principle less than the increase in amount of wafer area. However, up to the year 2000, the increasing functionality of the machinery had a much bigger impact than the increasing wafer size, and so the ratio of semiconductor equipment spending to semiconductor sales rose. In recent years, semiconductor manufacturing techniques have reached a relatively mature phase (although line-width transitions occur on the same regular schedule that they have historically, as we discuss in more detail in the technology section). We believe that the current 300mm transition is resulting in reduced capital costs. A 300mm wafer has more than 2x the area of a 200mm wafer, and so, more than twice the number of chips is made on a 300mm wafer than on a 200mm wafer.

(3) Semiconductor manufacturing has become more concentrated in a relatively small number of large players. Semiconductor foundries have grown faster than the chip industry overall as more companies become fabless, depending on foundries for their chip manufacturing. In addition, we think that over the past decade or so, the chip industry as a whole has shifted its priorities to focus more on profitability and capital efficiency than on raw growth. We expect that in the future, these factors could well lead to more pricing pressure on semiconductor equipment, as well as less duplication of equipment purchases, leading to more stable and higher capacity utilization in the semiconductor industry.

(4) In recent years a number of chip companies have suggested that transitions to more advanced technologies are becoming increasingly difficult to make, which might increase the capital intensity of the semiconductor industry. In particular, as we discuss in more detail in the “Selected Technology Topics” section of this report, difficulties with transitioning to a different color of light (shorter wavelength – EUV) in the cameras used to image semiconductor patterns has led to the need for multiple patterning. Multiple patterning involves the use of the most expensive pieces of semiconductor equipment, the lithography steppers, two or three times instead of once to transfer a single pattern layer onto a semiconductor wafer.

From Exhibit 15 it can be seen that in the early 1990s, semiconductor equipment spending was, on average, running at about 15% of IC sales. This number rose to more than 20% (with great volatility) in the late 1990s. In response to the downturn of 2001, the chip industry held down capital investment through 2002 and 2003, though the investment ratio rose in 2004 as demand strengthened. We think that many investors are under the mistaken impression that technology difficulties have led to the rise of capital intensity of the semiconductor industry in recent years and will continue to rise in the future. We think that the data show a long-term trend in the ratio of semiconductor equipment spending to IC sales that has been sloping downward from 2000 through today (2014). We believe this trend toward a lower percentage of capital reinvestment will continue through the next several years.

We think it is interesting, though, that the chip industry began to drive down the ratio of manufacturing equipment purchases to semiconductor sales, beginning in mid-2007, and with the downturn of 2009, the ratio fell to 7-8% in H1 2009, lower than at any other point in the preceding 19 years. While the ratio rebounded from mid-2009 to mid-2010, we think the huge and rapid drop in spending in H1 2009 shows the heightened sensitivity that chip companies have developed to the risks of excess capacity and excess inventory.

The very low ratio of reinvestment seen in 2008 and in H1 2009 is almost certainly far below the maintenance capex level, i.e., the level of capital spending needed for replacement of obsolete or aging equipment and other maintenance functions. As shown in the preceding Exhibit 11, worldwide chip capacity started to fall in December 2008 and dropped substantially in H1 2009. Since it takes time to install and qualify new equipment (on the order of weeks to months), capacity changes in any given quarter are a reflection of equipment purchases in previous quarters. We look at the fact that chip equipment investment levels were very low in H1 2009 as part of the reason for the declines in chip capacity through H2 2009 and into H1 2010. Similarly, rising, but still modest spending in 2010, led to worldwide chip capacity holding steady through most of 2010, but rising slowly toward the end of 2010 and into 2011.


23

Exhibit 16. North American Semiconductor Equipment Book-To-Bill Ratio

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

$0

$500

$1,000

$1,500

$2,000

$2,500

$3,000

$3,500

$4,000Jun‐91

Apr‐92

Feb‐93

Dec‐93

Oct‐94

Aug‐95

Jun‐96

Apr‐97

Feb‐98

Dec‐98

Oct‐99

Aug‐00

Jun‐01

Apr‐02

Feb‐03

Dec‐03

Oct‐04

Aug‐05

Jun‐06

Apr‐07

Feb‐08

Dec‐08

Oct‐09

Aug‐10

Jun‐11

Apr‐12

Feb‐13

Dec‐13

Book/B

ill

North American Chip Equipment ($MM)

Bookings Billings Book:Bill

Source: Semiconductor Equipment and Materials Institute and Wells Fargo Securities, LLC

Exhibit 16 shows North American semiconductor equipment bookings and billing (shipment) data as released by the Semiconductor Equipment and Materials Institute (SEMI). Our interest from a semiconductor point of view is more in the worldwide semiconductor equipment purchases, and we have used worldwide data for Exhibit 15 in calculating the ratio of semiconductor equipment purchases to IC sales. However, the North American numbers track the worldwide numbers closely as far as overall trend goes. The North American data are issued by SEMI some weeks ahead of the worldwide data, and we believe that it is the more widely tracked and discussed information and so, we have shown it here.

As shown in Exhibit 4, by 2004, semiconductor revenue had recovered to reach the peak first hit in 2000 and then continued to rise from 2004 through 2007. In 2010, semiconductor revenue passed its prior 2007 peak and was more than 20% higher than during the year-2000 peak, and chip sales are on track to hit a new peak in 2014. However, Exhibit 16 shows that in 2014, North American semiconductor equipment purchases are running at less than half their year 2000 levels. Worldwide semiconductor equipment data show a similar qualitative trend, with worldwide semiconductor equipment sales in 2014 being about a third below year 2000 levels. The quantitative difference in the U.S. versus global semiconductor equipment trend arises in part because some important segments of semiconductor equipment with strong secular growth characteristics, in particular, lithography (machines that project the circuit patterns), are served by non-U.S. companies (e.g., ASML in the case of lithography).

Exhibit 16 also shows how aggressively the chip industry responded to the downturn of 2008, by cutting semiconductor equipment purchases in early 2009 down to levels comparable to what was last seen in the early 1990s. Similar caution can be seen in the sharp fall of semiconductor bookings and semiconductor equipment book-to-bill in mid-2011 and mid-2012, in response to ongoing softness in semiconductor end-market demand.


24

The Rise Of The Foundries

The semiconductor foundries are companies that manufacture (process) semiconductor wafers for fabless chip companies. The trend to outsource manufacturing is growing steadily. In 2002, foundries accounted for 9-11% of all semiconductor processing (in terms of wafer-equivalent starts), a percentage that had risen to about 14-15% by H1 2008. Foundry wafer production grew at a 21% per year rate from 2002 through mid-2008, while overall semiconductor wafer production grew 11%. By 2013, foundries were responsible for about 20%-30% of all worldwide semiconductor production.

The trade group Semiconductor International Capacity Statistics (SICAS) gathered from information provided by the member semiconductor companies of SICAS. Unfortunately, through 2011, a number of the regular contributors of data to SICAS decided to stop providing numbers, with the result being that the group stopped publishing its worldwide semiconductor capacity information.

The foundry model achieves the following:

The foundries, by aggregating the business of several fabless companies, can achieve the scale that is required for the large investments in fabs and technology development.

The foundries take on substantial capital risk, but in return, do not have product development and product competition risk.

Exhibit 17 shows the largest semiconductor foundries. Exhibit 17. Revenue Share For IC Foundries (2013)

TSMC, 46%

GlobalFoundries***, 10%UMC, 9%

Samsung, 9%

SMIC*, 5%

Powerchip**, 3%

Vanguard, 2%

Huahong Grace, 2%

Dongbu, 1%

TowerJazz, 1%

IBM, 1%MagnaChip, 1%

WIN, 1% Other, 9%

*Does not include Wuhan Xinxin (now XMC) for 2013 **Powerchip transitioned from an IDM foundry to a pure-play foundry in 2013 ***In October 2014 IBM announced a deal in which it is transferring its semiconductor manufacturing operations to GlobalFoundries. If this deal is successfully closed, the size of GlobalFoundries will increase by more than the 1% foundry revenue share that we have shown in our pie chart for IBM, because GlobalFoundries will take over the manufacturing of IBM’s fairly substantial internal chip needs which are not reflected in IBM’s foundry revenues. Source: IC Insights' The McClean Report 2014 and Wells Fargo Securities, LLC


25

The world’s largest foundry, Taiwan Semiconductor Manufacturing Corporation (TSMC) was formed in 1986. Today the company accounts for almost half of the IC foundry market. Since the foundry business is capital-intensive, we think size is helpful in maintaining leading-edge technology. Globalfoundries is the second-largest foundry, with about a 10% market share.

GlobalFoundries was formed in 2009 by AMD teaming up with an investor (ATIC, the investment wing of the Abu Dhabi Government), to spin out its manufacturing operations into a joint venture. Since AMD owned a stake in GlobalFoundries and through 2009, AMD was essentially its sole customer, GlobalFoundries did not really look like a true foundry in a business sense. However, at the beginning of 2010, Chartered Semiconductor was acquired and folded into GlobalFoundries to create a foundry of size that is comparable with UMC’s. In March 2012, AMD announced that it had divested its remaining stake in GlobalFoundries. In October 2014 IBM announced an agreement in which it plans to transfer its semiconductor manufacturing operations to GlobalFoundries (and pay GlobalFoundries $1.5 billion to do this!) If this deal is successfully closed, the size of GlobalFoundries should increase by more than the 1% foundry revenue share that we have shown in our pie chart for IBM because GlobalFoundries is to take over the manufacturing of IBM’s fairly substantial internal chip needs, which are not reflected in IBM’s foundry revenue.

Samsung is a leading manufacturer of memory chips and also does some chip foundry work. In recent years, Samsung’s foundry business has grown dramatically, driven by the fact that Samsung manufactured all of Apple’s processor chips (designed by Apple) for Apple’s iPhone and iPad products through most of 2013. In 2013, Samsung accounted for about 9% of world foundry revenue, down from 11% in 2012. However, we believe Apple moved a large portion of its processor business away from Samsung to TSMC in late 2013, hurting Samsung’s global foundry share, which we think might fall further in 2014. However, we think that Samsung might regain some of the Apple foundry business in 2015.

Intel has begun to offer foundry services. Intel has indicated that it does not wish to be an all-purpose foundry for a broad range of chip companies, and specifically, that Intel has no intention of providing foundry services for companies that it considers its competitors. We expect that in the near term, Intel’s foundry volume will likely be very small. However, we believe that Intel is very interested in competing for Apple’s foundry business. If Intel does win Apple or any other substantial foundry customer, this could give Intel meaningful worldwide foundry market share. Altera has already announced that it will be using Intel to manufacture its most advanced high-end products, but we do not expect Altera to begin ramping its foundry business at Intel in any volume until 2016, and even then, at just one portion of Altera’s total foundry needs, the Altera business would still represent only a small percent of the global foundry market.

TSMC and UMC, since they are Taiwanese companies, report sales monthly, which provides a good monitor of chips produced for the fabless semiconductor companies. Exhibit 18 shows monthly sales for these two companies combined, while Exhibit 19 shows year-over-year growth. The foundry segment has higher growth, but more volatility than the overall semiconductor industry.


26

Exhibit 18. Taiwanese Foundry (TSMC+UMC) Monthly Revenue

$0

$200

$400

$600

$800

$1,000

$1,200

$1,400

$1,600

$1,800

$2,000

$2,200

$2,400

$2,600

$2,800

$3,000

$3,200

Dec‐93

Mar‐94

Jun‐94

Sep‐94

Dec‐94

Mar‐95

Jun‐95

Sep‐95

Dec‐95

Mar‐96

Jun‐96

Sep‐96

Dec‐96

Mar‐97

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Mar‐99

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Feb‐00

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Nov‐00

Feb‐01

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Nov‐01

Feb‐ 02

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Jul ‐10

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Dec‐11

Mar‐12

Jun‐12

Sep‐12

Dec‐12

Mar‐13

Jun‐13

Sep‐13

Dec‐13

Mar‐14

Jun‐14

Sep‐14

Revenue (US$MM)

Pre-UMC Consolidation

Source: Company reports and Wells Fargo Securities, LLC estimates Exhibit 19. Taiwanese Foundry (TSMC+UMC) Monthly Revenue (Year-Over-Year Growth)

(80%)

(60%)

(40%)

(20%)

0%

20%

40%

60%

80%

Dec‐00

Mar‐01

May‐01

Aug‐01

Nov‐01

Feb‐02

May‐02

Aug‐02

Nov‐02

Feb‐03

May‐03

Aug‐03

Nov‐03

Feb‐04

May‐04

Aug‐04

Nov‐04

Feb‐05

May‐05

Aug‐05

Nov‐05

Feb‐06

May‐06

Aug‐06

Oct‐06

Jan‐07

Apr‐07

Jul‐07

Oct‐07

Jan‐08

Apr‐08

Jul‐08

Oct‐08

Jan‐ 09

Apr‐09

Jul‐09

Oct‐09

Jan‐10

Apr‐10

Jul‐10

Oct‐10

Jan‐11

Apr‐11

Jul‐11

Oct‐11

Jan‐12

Apr‐12

Jul‐12

Sep‐12

Dec‐12

Mar‐13

Jun‐13

Sep‐13

Dec‐13

Mar‐14

Jun‐14

Sep‐14

Yr/Yr % Chan

ge

Source: Company reports and Wells Fargo Securities, LLC estimates

Foundry sales are not, in fact, equivalent to semiconductor sales, but they are roughly equivalent to semiconductor cost of goods sold (COGS) since the fabless companies report the cost of the wafers they buy from the foundries on their cost of goods line in their income statements (though cost of goods contains other elements, too, including the packaging and test costs of the chips once the foundries have delivered the wafers). A wafer typically takes about 13 weeks to process, and this can be the bulk of the cost of a semiconductor chip. The packaging and testing of the chips takes a week or two. Some fabless semiconductor companies, such as Altera, keep the bulk of their inventory in wafer form (this is referred to as being in die bank since the chips that are cut from the wafers are called dice, die in singular).


27

Exhibit 20. Average Wafer Price By Foundry (200mm Equivalents)

$600

$800

$1,000

$1,200

$1,400

$1,600

$1,800

$2,000

Ave

rag

e S

elli

ng

Pri

ce (

US

$/8

In E

qu

iv W

fr)

TSMC Wafer ASP UMC Wafer ASP

Source: Company reports and Wells Fargo Securities, LLC Exhibit 20 shows average wafer pricing at each foundry (the price at which the foundries sell the fully processed wafers to the fabless companies). The average wafer price is above $1,000 for an 8-inch equivalent wafer (i.e., 12-inch wafers have more than double this price since they have more than double the area). We believe, however, that prices vary by a fair amount, depending on what technology node the wafer is processed.

Exhibit 21 shows TSMC’s wafer sales by technology. About 60% of TSMC’s sales are for the most advanced technologies, 40nm, 28nm, and 20nm line widths (an explanation of line widths is provided further on in this report). Many fabless companies do not need cutting-edge technology, and so they buy wafers fabricated with somewhat older (and less expensive) technology nodes.


28

Exhibit 21. TSMC Wafer Sales By Technology

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%Q

1 0

1

Q3

01

Q1

02

Q3

02

Q1

03

Q3

03

Q1

04

Q3

04

Q1

05

Q3

05

Q1

06

Q3

06

Q1

07

Q3

07

Q1

08

Q3

08

Q1

09

Q3

09

Q1

10

Q3

10

Q1

11

Q3

11

Q1

12

Q3

12

Q1

13

Q3

13

Q1

14

Q3

14

0.50um+

0.25/0.35um

0.15/0.18um

0.11/0.13um

90nm

65nm

40nm

28nm

20nm

Source: Company reports and Wells Fargo Securities, LLC


29

Semiconductor Inventory And The Electronics Supply Chain

It is important for semiconductor companies to carry some inventory and for there to be adequate inventory in the supply chain (e.g., at distributors, contract manufacturers, etc.), so that demand for product can be met in an efficient manner. If inventory levels are too low, that can lead to lost business. On the other hand, investors can be very sensitive to the risk of excess inventory building up.

Exhibit 22 illustrates places in the electronics supply chain where excess semiconductor inventory can build up.

Exhibit 22. Semiconductor Supply Chain

Foundry Chip Company (inc. fabless)

Semiconductor Distributor

Contract Manufacturer

Wireless Communications OEM

Electronics Resellers, Distributors, and Retailers

End Customer

Computer Hardware OEM Communications Infrastructure OEM

Source: Wells Fargo Securities, LLC Excess inventory can affect sales and profitability of semiconductor companies in several ways:

Excess inventory at chip companies can lead to inventory write-downs. If a chip company is holding too much inventory and the inventory gets obsolete or the value of the inventory drops excessively (e.g., for a commodity-like memory), the company may have to take inventory write-downs that drive up cost of goods in a given quarter. Memory companies have this risk, and microprocessor companies appear to sometimes get affected, too. There is a class of companies, like analog companies and PLD companies, that has products with long life cycles and fairly stable pricing. Such companies have less risk of needing inventory write-downs. However, there have been times in the past, for example, during the downturn of 2000-01, when even companies that we would view as having a lower risk of inventory write-downs (e.g., PLD companies like Altera and Xilinx) did take inventory charges.


30

Excess inventory at chip manufacturers can lead to factory underutilization. If a company that makes its own chips builds up too much inventory internally, this can lead to a need to cut back on production while the excess inventory is being worked down. This can lead to underutilization of the fabs, which results in either an increase in the cost of each chip that is manufactured, or “underutilization charges” being taken against cost of goods. Companies with fabs that manufacture their own chips have this risk, whereas fabless companies, in general, do not.

Excess inventory at distributors can sometimes affect chip revenue. Excess inventory at distributors can lead to cutbacks in orders from distributors as they work to reduce their inventory levels. Inventory at distributors is of particular importance to analog and PLD companies that sell a high percentage (sometimes as much as 90%) of their product through distribution.

o Companies that recognize revenue on sell-in to distribution can have their sales affected by distributors driving down their inventory levels. The converse is true, too. When inventory levels at distributors are lean at the end of a downturn with business gathering momentum, companies that recognize revenue on sell-in to distribution get the double benefit of increasing end-customer demand, as well as inventory builds in distribution.

o Companies that recognize revenue on sell-through from distribution are not at risk of a revenue hit. For such companies, inventory at distribution can look similar to internal inventory at the company from a financial point of view. In such cases, excess inventory at distribution creates the similar problems to excess internal inventory. Altera, for example, often discusses its inventory targets in terms of internal inventory + inventory at distribution.

Excess inventory at systems manufacturers can affect chip revenue. Systems manufacturers (makers of electronics goods like PCs, wireless handsets, etc.) include contract manufacturers (companies that make things for other companies), as well as original equipment manufacturers, companies that both make and sell their own products. If there is excess chip inventory at systems manufacturers, this can lead to the systems manufacturers slowing their chip purchases while they work down their excess inventory, resulting in a drop in revenue for the chip companies.

Excess systems inventory at systems resellers, systems distributors, and retailers can affect chip revenue. Sometimes lack of demand can lead to a buildup of inventory in electronics systems that have already been fully manufactured. This can be a particular risk for products sold to consumers in the second half of the year. If there is weakness in consumer demand during the holiday season, there can be excess inventory of finished electronics goods in stores in the new year. Excess systems inventory results in a drop in orders to systems manufacturers, which, in turn, results in a drop in demand for chips and a drop in chip revenue.

Exhibit 23 though Exhibit 26 show a sample of inventory graphs related to various parts of the semiconductor supply chain that we monitor.

In the downturn of 2001, inventory spiked at various points in the electronics supply chain and, in particular, excess inventory built up at chip distributors and electronic systems contract manufacturers. This excess inventory took about two years to work down, creating a significant headwind working against a recovery in chip demand through 2001 and 2002.

Perhaps in part as a response to the inventory issues that developed in 2001, over the past few years there has been a trend toward more internal inventory at chip companies and less at distributors and contract manufacturers (as measured in days of inventory). This reduces the risk that excess inventory might build up at distributors and contract manufacturers, catching the chip manufacturers unaware.

We believe that the memory of problems of 2001-02 may have been a factor behind the very decisive action taken by participants in the electronics supply chain to cut back production and reduce inventory in H2 2008 and in early 2009, when the impact of the global economic issues became clear. As shown in our inventory graphs, the supply chain did successfully avoid a repeat of the inventory problems of 2001. We credit the skillful management of inventory with supporting chip pricing and paving the way for the rebound in sequential semiconductor shipment growth, which began around Q2 2009.


31

In the second half of 2011, concerns over a variety of factors including, we think, global economic concerns and also disruptions to disk drive supply associated with flooding in Thailand, resulted in an inventory correction throughout the electronics supply chain that extended through 2012.

At the time of writing of this report (November 2014), we believe that exiting the third calendar quarter of 2014, inventory levels were slightly elevated, due in part to a normal seasonal lift in builds and also to the somewhat softer than seasonal outlook many chip companies have indicated heading into the December 2014 quarter.

A more detailed discussion of inventory trends and the various companies that we monitor to track inventory is beyond the scope of this primer, but is contained in our Inventory Review, which we typically issue quarterly.

Exhibit 23. Large Chip Manufacturers--Days Of Inventory And Absolute Inventory

(30%)

(20%)

(10%)

0%

10%

20%

30%

40%

50%

60%

70%

0

10

20

30

40

50

60

70

80

90

100

Jun

-99

Se

p-9

9D

ec-9

9M

ar-0

0Ju

n-0

0S

ep

-00

Dec

-00

Mar

-01

Jun

-01

Se

p-0

1D

ec-0

1M

ar-0

2Ju

n-0

2S

ep

-02

Dec

-02

Mar

-03

Jun

-03

Se

p-0

3D

ec-0

3M

ar-0

4Ju

n-0

4S

ep

-04

Dec

-04

Mar

-05

Jun

-05

Se

p-0

5D

ec-0

5M

ar-0

6Ju

n-0

6S

ep

-06

Dec

-06

Mar

-07

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-07

Se

p-0

7D

ec-0

7M

ar-0

8Ju

n-0

8S

ep

-08

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-08

Mar

-09

Jun

-09

Se

p-0

9D

ec-0

9M

ar-1

0Ju

n-1

0S

ep

-10

Dec

-10

Mar

-11

Jun

-11

Se

p-1

1D

ec-1

1M

ar-1

2Ju

n-1

2S

ep

-12

Dec

-12

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-13

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-13

Se

p-1

3D

ec-1

3M

ar-1

4Ju

n-1

4S

ep

-14

Yr/

Yr

% C

han

ge

Lar

ge

Ch

ip M

anu

fact

ure

rs' D

ays

Of

Inve

nto

ry

Days Of Inventory 3-Year Quarter Average Yr/Yr % Change

(30%)

(20%)

(10%)

0%

10%

20%

30%

40%

50%

60%

$0

$1,500

$3,000

$4,500

$6,000

$7,500

$9,000

$10,500

$12,000

$13,500

Mar

-99

Jun

-99

Se

p-9

9D

ec-9

9M

ar-0

0Ju

n-0

0S

ep

-00

Dec

-00

Mar

-01

Jun

-01

Se

p-0

1D

ec-0

1M

ar-0

2Ju

n-0

2S

ep

-02

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-02

Mar

-03

Jun

-03

Se

p-0

3D

ec-0

3M

ar-0

4Ju

n-0

4S

ep

-04

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-04

Mar

-05

Jun

-05

Se

p-0

5D

ec-0

5M

ar-0

6Ju

n-0

6S

ep

-06

Dec

-06

Mar

-07

Jun

-07

Se

p-0

7D

ec-0

7M

ar-0

8Ju

n-0

8S

ep

-08

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-08

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-09

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-09

Se

p-0

9D

ec-0

9M

ar-1

0Ju

n-1

0S

ep

-10

Dec

-10

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-11

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-11

Se

p-1

1D

ec-1

1M

ar-1

2Ju

n-1

2S

ep

-12

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-12

Mar

-13

Jun

-13

Se

p-1

3D

ec-1

3M

ar-1

4Ju

n-1

4S

ep

-14

% C

han

ge

Lar

ge

Ch

ip M

anu

fact

ure

rs' I

nve

nto

ry (

$MM

)

Inventory Yr/Yr % Change Qtr/Qtr % Change

* Compiled data are from INTC, TXN, MXIM, MU, STM, and LLTC. **Micron has a fiscal quarter that ends one month before the calendar quarter. We have mapped each Micron number into the closest calendar quarter. Source: Company reports and Wells Fargo Securities, LLC estimates


32

Exhibit 24. Fabless Chip Company--Days Of Inventory And Absolute Inventory

(40%)

(30%)

(20%)

(10%)

0%

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30%

40%

50%

60%

0

10

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100Ju

n-0

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ep

-00

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ec-0

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ar-0

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n-0

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ep

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ep

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ep

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ep

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ec-0

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ep

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n-1

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ep

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p-1

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4Ju

n-1

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ep

-14

Yr/

Yr

% C

han

ge

Fab

less

Day

s o

f In

ven

tory

Days of Inventory 3-Year Quarter Average Yr/Yr % Change

(50%)

(30%)

(10%)

10%

30%

50%

70%

90%

110%

130%

150%

0200400600800

1000120014001600180020002200240026002800300032003400360038004000

Jun

-00

Se

p-0

0D

ec-0

0M

ar-0

1Ju

n-0

1S

ep

-01

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-01

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-02

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-02

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p-0

2D

ec-0

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ar-0

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n-0

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ep

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Se

p-0

4D

ec-0

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ar-0

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n-0

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ep

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p-0

6D

ec-0

6M

ar-0

7Ju

n-0

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ep

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p-0

8D

ec-0

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ar-0

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n-0

9S

ep

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-10

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-10

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p-1

0D

ec-1

0M

ar-1

1Ju

n-1

1S

ep

-11

Dec

-11

Mar

-12

Jun

-12

Se

p-1

2D

ec-1

2M

ar-1

3Ju

n-1

3S

ep

-13

Dec

-13

Mar

-14

Jun

-14

Se

p-1

4

% C

han

ge

Fab

less

Inve

nto

ry (

$MM

)


*Compiled data are from Xilinx, Altera, Broadcom, Qualcomm, and Nvidia. Source: Company reports and Wells Fargo Securities, LLC estimates


33

Exhibit 25. Semiconductor Distributors--Days Of Inventory And Absolute Inventory

(40%)

(30%)

(20%)

(10%)

0%

10%

20%

30%

40%

50%

60%

0

10

20

30

40

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60

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90

100Ju

n-0

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ep

-00

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-01

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p-0

1D

ec-0

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ar-0

2Ju

n-0

2S

ep

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p-0

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ec-0

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ar-0

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n-0

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ep

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p-0

5D

ec-0

5M

ar-0

6Ju

n-0

6S

ep

-06

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-06

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-07

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-07

Se

p-0

7D

ec-0

7M

ar-0

8Ju

n-0

8S

ep

-08

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-08

Mar

-09

Jun

-09

Se

p-0

9D

ec-0

9M

ar-1

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n-1

0S

ep

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p-1

1D

ec-1

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ar-1

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n-1

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ep

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p-1

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ep

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Yr/

Yr

% C

han

ge

Ch

ip D

istr

ibu

tor

Day

s o

f In

ven

tory

Days of Inventory 3-Year Quarter Average Yr/Yr % Change

(50%)

(40%)

(30%)

(20%)

(10%)

0%

10%

20%

30%

40%

50%

60%

70%

80%

$0

$500

$1,000

$1,500

$2,000

$2,500

$3,000

$3,500

$4,000

$4,500

$5,000

$5,500

$6,000

$6,500

Mar

-99

Jun

-99

Se

p-9

9D

ec-9

9M

ar-0

0Ju

n-0

0S

ep

-00

Dec

-00

Mar

-01

Jun

-01

Se

p-0

1D

ec-0

1M

ar-0

2Ju

n-0

2S

ep

-02

Dec

-02

Mar

-03

Jun

-03

Se

p-0

3D

ec-0

3M

ar-0

4Ju

n-0

4S

ep

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Dec

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Mar

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Jun

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Se

p-0

5D

ec-0

5M

ar-0

6Ju

n-0

6S

ep

-06

Dec

-06

Mar

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Jun

-07

Se

p-0

7D

ec-0

7M

ar-0

8Ju

n-0

8S

ep

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Dec

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Mar

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-09

Se

p-0

9D

ec-0

9M

ar-1

0Ju

n-1

0S

ep

-10

Dec

-10

Mar

-11

Jun

-11

Se

p-1

1D

ec-1

1M

ar-1

2Ju

n-1

2S

ep

-12

Dec

-12

Mar

-13

Jun

-13

Se

p-1

3D

ec-1

3M

ar-1

4Ju

n-1

4S

ep

-14

% C

han

ge

Ch

ip D

istr

ibu

tors

' In

ven

tory

($M

M)


*Compiled data are from Arrow and Avnet. However, in addition to semiconductors and components, some portion of Avnet and Arrow’s total sales are derived from computer products, services, and computer components. Therefore, the data in these graphs really reflect a blend of semiconductor and computer systems business. Source: Company reports and Wells Fargo Securities, LLC estimates


34

Exhibit 26. Contract Manufacturers--Days Of Inventory And Absolute Inventory

(40%)

(30%)

(20%)

(10%)

0%

10%

20%

30%

40%

50%

60%

0

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*Compiled data are from Jabil, Flextronics, Sanmina, Celestica, and Benchmark Electronics. Jabil has a fiscal quarter that ends one month before each calendar quarter. Source: Company reports and Wells Fargo Securities, LLC estimates


35

Semiconductor Segments

Exhibit 27 through Exhibit 29 show, in a number of different ways, segment breakouts for integrated circuits. We discuss some of what we consider to be the more important sub-segments further on in this section.

As discussed, semiconductors can be grouped in three broad categories:

Integrated circuits (an entire electronic circuit on a single chip);

Discrete devices (simple, single device products, as opposed to a complete circuit); and

Optoelectronics (semiconductors that either produce, or sense, light).

ICs account for more than 82% of semiconductor sales. There are three main groups of ICs:

Logic (chips that can think);

Analog (chips that act as an interface between the real world and the logic chips); and

Memory (chips that can remember things).

Most logic is digital logic and most memory is digital. In other words, logic chips and memory chips are designs to deal with two types of information: a “1” or a “0”. Analog, on the other hand, is a type of chip that can handle a continuous signal.


36

Exhibit 27. Semiconductor Market Breakdown

Semiconductors Integrated Circuits Logic Specialized Logic (ASICs & ASSPs)

Micro-components Microprocessor

Microcontroller

DSP

Standard Logic Standard Cell and FPLD

Display Drivers

General Purpose

MOS Gate Array

Digital Bipolar

Memory Volatile Memory DRAM

SRAM

Non-Volatile Memory Flash NAND Flash

NOR Flash

Mask & EPROM

Other Memory

Analog Application Specific Analog

General Purpose Analog

Optoelectronics, Sensors, and Actuators

Discrete Components Transistors

Rectifiers

Diodes

Thyristors

Other Discretes Source: Semiconductor Industry Association and Wells Fargo Securities, LLC estimates

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37

Exhibit 28. IC Segments--2013 Sales

Source: Semiconductor Industry Association, Wells Fargo Securities, LLC estimates

Logic57%

Analog16%

Memory27%

$252 billion

MPU29%

MCU10%

DSP2%

Gen. MOS Logic &c.

59%

$145 billion

Volatile53%

Non-Volatile

44%

Other Memory

3%

$67 billion

DRAM98%

SRAM2%

$36 billionNOR Flash8%

NAND Flash92%

$30 billion

General Purpose Analog40%

Application Specific

60%

$40 billion

Amplifiers16%

Interface12%

Power Management

58%

Signal Conversion

14%

$16 billion

Consumer8%Computer &

Peripherals9%

Communication49%

Automotive24%

Industrial & Other10%

$24 billion


38

Exhibit 29. Types Of Integrated Circuits (Percent Of Sales In 2013)

Other logic34%

MPU16%

Analog16%

MCU6%

DSP1%

DRAM14%

NAND Flash11%

NOR Flash1%

Other Memory1%

Source: Semiconductor Industry Association, Wells Fargo Securities, LLC

Analog

Analog semiconductors can be broken out into two main sub-segments: standard and application-specific.

Standard linear chips. These are generic products that are often sold through distribution.

Application-specific analog. These are chips that are designed for a specific customer or device. This category includes mixed-signal analog chips, which combine analog and digital capability.

There are four main categories of standard linear chips:

Power management. These are the chips that control the distribution of power through an electronic systems, making sure that the voltages are the right voltages for each chip and that there is enough current for each chip’s needs.

Data signal conversion chips (see Exhibit 30). There are two main types of data conversion chips:

o Analog-to-digital converters (A/D converters). These take a continuous analog signal and convert it to a stream of digital numbers by making measurements of the height (voltage of the signal) at regular time intervals.

o Digital-to-analog converters (D/A converters) These do the opposite; they take a stream of numbers and make these into a continuous signal.

Data converters sit at the edge of many electronic digital systems. For example, today’s cellphones are all based on digital standards. When one speaks into a cellphone, the voice is a continuous signal. This has to be converted to a stream of digital numbers for the digital chips inside the cellphone to process the information and an A/D converter does this. At the other end, the receiving cellphone has a stream of numbers that has to be converted back into a sound that the listener can hear. This job is done by a D/A converter.

Interface chips. Interface chips are analog chips that provide the interface onto standardized communications signal lines. They are the chips responsible for driving the electrical voltages or currents down the lines. For example, in a computer, there would be some PCMCIA chips for driving signals down a PCMCIA bus.


39

Amplifiers. These are analog chips that make electrical signals bigger, while maintaining the same shape as the original electrical signal.

Exhibit 30. A/D And D/A Converters 5 = 0101

7 = 0111

A/D Converter

0101, 0111………

5 = 01017 = 0111

D/A Converter

0101, 0111………

5 = 01017 = 0111

5 = 01017 = 0111

A/D Converter

0101, 0111………

5 = 01017 = 0111

5 = 01017 = 0111

D/A Converter

0101, 0111………

Source: Wells Fargo Securities, LLC Texas Instruments, Maxim, Linear, and Analog Devices are companies that make standard linear chips.

Communications applications often use application-specific solutions. A number of semiconductor companies that are thought of as “communications chip” companies, rather than “analog” make mixed-signal chips that fall into this category. High-frequency or radio frequency chips, for applications such as wireless and microwave applications, are analog chips, too; so, while companies that make this class of chips (e.g., Skyworks, RF Micro Devices, Triquint) are also producing analog chips, they are not usually described as analog companies.

As indicated by their relatively low ASP (roughly $0.35-0.45), analog chips are generally fairly small. Consistent precise performance is often important for analog chips, but in terms of the number of transistors and other circuit elements, analog chips tend to be relatively simple.

Logic

Although the manufacturing technology for making logic chips is similar for most logic sub-segments, the design techniques differ and so, semiconductor companies that make logic chips often specialize in one or a small number of sub-segments.

Logic--processors. Processors are chips that can think and also have a fair amount of programming flexibility.

Microprocessors. Microprocessors are general-purpose thinking chips. Microprocessors tend to be large chips that use millions to billions of transistors and other circuitry elements, and consequently, they are among the highest-priced ICs. Microprocessors have an ASP of about $100 (though at the high end, microprocessor prices can rise to more than $1,000.00). PC microprocessors require cutting-edge manufacturing technology. Intel and AMD are the main manufacturers of microprocessors (x86 microprocessors) for PCs, while IBM makes the PowerPC microprocessor. PowerPC used to be used in Apple Computers, but when Apple transitioned to Intel-based microprocessors, PowerPC usage shifted primarily to servers and embedded applications. ARMS and MIPS are two popular non-x86 processor architectures used in consumer and communications applications such as cell phones, digital TVs, routers, and voice over Internet protocol (IP).


40

Digital signal processors (DSP). DSPs are processors that are optimized for making sense of communications signals. One important application for DSPs is in wireless handsets, but DSPs are also used in a variety of communication, consumer, industrial, and other end markets. DSPs are moderately complicated chips and have an ASP of about $6.00. Texas Instruments, Analog Devices, and Freescale make DSPs.

Microcontrollers. Microcontrollers are processors that are used for simple control applications in a wide range of devices, from washing machines and microwave ovens, to cars and industrial machinery. A microcontroller is used when the amount of thinking needed is less than what a full-fledged microprocessor might provide. Microcontrollers are relatively simple chips and generally do not require very advanced manufacturing technology. They have an ASP of about $0.88. Examples of companies making microcontrollers include Microchip, Freescale, Texas Instruments, Infineon, and Philips. The processing horsepower of a microcontroller is dictated by word length (number of bits). Eight-bit microcontrollers currently represent the low end of the market, and we think the market will continue to migrate toward 32-bit over the next several years. Many microcontroller companies have adopted the ARM architecture for 32-bit offerings.

Other processors. Two examples of other processors are graphics processors and network processors. Graphics processors are processors optimized for generating or processing images (i.e., graphics rendering). One important application for these chips is in computers. Graphics processors tend to be quite large, complicated chips, and command prices of tens of dollars. Nvidia and AMD (ATI) are companies that make graphics processors. Network processors are processors optimized for handling data traffic in computer and communications networks. Makers of network processors include Broadcom, LSI (Agere), and PMC-Sierra.

Standard logic. Standard logic chips are logic chips that are less flexible than microprocessors. They do logic operations (i.e., they think), but in general, each specific type of standard logic chip is designed to always do the same specific logic operation, unlike processors, which run software programs that determine what logic operations they perform. Even programmable logic devices (PLD) are a type of standard logic, which are designed to always do the same thing once they have been configured with a specific program.

Programmable logic devices (PLD). Programmable logic devices are devices that are not committed to any specific logic operation; however, they can be configured with programming. This is different from the way processors use software programs. Processors have circuitry that is designed in a specific way and then this circuitry executes instructions according to its software program. PLDs are chips that obtain the actual configuration of their circuitry (what is connected to what) from a program. Although in principle they can be reprogrammed, each chip is typically programmed once and then operates like a chip with fixed logic that always does the same thing. Field programmable gate arrays (FPGA) and complex programmable logic devices (CPLD) are types of PLDs. FPGAs are typically used for prototyping or relatively low-volume applications. Because PLDs can be configured to perform a wide range of logic operations, they are often used instead of making a custom design of a chip, an application-specific integrated circuit (ASIC). PLDs have a wide range of complexity; some of the high-end FPGAs are among the largest chips made. PLD prices range from a few dollars to several hundred, depending on the size and level of complexity. Xilinx and Altera are the two largest PLD companies, with a combined market share of 90% of the FPGA and PLD market. Smaller PLD companies include Lattice, Microsemi, Atmel, Chengdu Sino Microelectronics System, and Cypress Semiconductor.

Standard logic. This is a catch-all describing a fairly broad range of standard logic chips that are neither processors, nor PLDs. Standard logic chips tend to be fairly simple chips. A wide range of companies make standard logic chips, including Texas Instruments.

ASICs and applications-specific standard products (ASSP). ASICs are chips that are custom designed for a specific end user (e.g., Cisco designs many of its own ASICs). ASSPs are chips that are designed for a specific application (as opposed to standard logic, which can be used for multiple applications), but not just for one customer. The term ASSP is a fuzzy one and many chips that are termed ASSP might fall into the analog group as mixed-signal chips or be considered standard logic.


41

Memory

DRAM and NAND flash are the two significant semiconductor memory segments, though there are a number of other (legacy) types of memory that are in secular decline.

There are two main types of semiconductor memory:

(1) Volatile memory. Volatile memory forgets what it was supposed to remember when the power is switched off. However, it is relatively easy to write information into volatile memory and to retrieve the information from it; so volatile memory is used as the main working memory in a system such as a PC. The two main types of volatile memory are DRAM and static random access memory (SRAM), though from an investment point of view, we believe DRAM is by far the more important of the two, with many major companies being involved in DRAM, whereas SRAM is made by a fistful of fairly small companies.

(2) Nonvolatile memory. Nonvolatile memory, on the other hand, remembers what it is supposed to remember when the power is switched off. Traditionally, nonvolatile memory has been used for permanent code storage in systems. For example, in a PC there is a small flash chip that contains the PC BIOS, that is, all the crucial information a PC needs to know when it is being switched on. Similarly, in a cellphone there is a flash chip that contains the code information (e.g., what the cellphone needs to know about the global system for mobile [GSM] standard or code division multiple access [CDMA] standard so that it can interpret the signals it receives). More recently, nonvolatile memory has also found a place in the storage of data, such as photographs taken with digital photography. In general, it is more difficult to write information to nonvolatile memory than to volatile memory, which is one reason that volatile memory is still used in many electronic systems. The main type of nonvolatile memory is flash memory, of which there are two types: NOR and NAND flash. Both of these are important in terms of total volume of sales, but NAND flash has a strong growth dynamic, whereas NOR flash does not. There are a number of legacy types of nonvolatile memory, none of which we believe are particularly important from an investment point of view since they are made by a small number of fairly small companies.

Volatile Memory

DRAM. In a PC, the information is initially loaded into the dynamic random access memory from the hard drive and also some information is provided by the microprocessor. It is “dynamic” because even when the power is switched on, it forgets what it is supposed to remember and so each memory cell has to be “refreshed.” Each DRAM chip contains circuitry to do this refresh tens to hundreds of times per second. It is “random access” because any information can be retrieved from any place in the memory at a given time (as opposed to serial, in which memory locations have to be looked at one after another in a certain order; NAND flash is serial to some extent). DRAM memories come in different sizes. A typical DRAM memory chip for a PC might be 4 Gigabits (Gigabit = Gb= 1 billion bits). This means that the chip can remember 4 billion ones or zeroes. Most electronic systems, including PCs, have memory specified in bytes, not bits. A byte equals eight bits. A 4-gigabyte (GB) PC might have eight different 4Gb DRAM chips in it. DRAM chips come in all sizes, from 64 million bits (Mb)( it is possible to get smaller memories, too) to 4 Gb. DRAM chips are commodities (in principle, a 1 Gb chip works exactly the same, regardless of which company one buys it from) and so the price tends to be very volatile. Also, as technology progresses, more bits can be jammed on a chip, and so, for the same price it is possible to buy a chip with more bits. At the time of writing this report, a 4 Gb DRAM chip cost around $4.00 (we have graphs with pricing information further on in this report.) Samsung, Qimonda (Infineon), Hynix, Elpida, and Micron are some of the bigger DRAM companies.

SRAM. SRAM is “static” because while the power stays on, it remembers what it is supposed to remember (it does not need a refresh). Static random access memory has traditionally been used for very high-performance applications, when very fast access to the information in the memory has been needed. SRAM is still used in communications systems, but its general use is less and less widespread. Cypress Semiconductor, Renesas, and Integrated Silicon Solutions are some companies that still make SRAM.


42

Non-volatile Memory

NAND and NOR flash. “Flash” is the name of a type of memory cell (something that can store a 1 or a 0). “NAND” and “NOR” refer to the logic functions (Not AND) and (Not OR), which describe the circuitry that a flash chip uses to access the memory locations. Because of the difference in memory access circuitry, NOR flash is more expensive than NAND flash and offers faster access to the memory. The largest use of NOR flash today is in cellphones for code storage. NAND flash is used when large amounts of information are to be stored and price is unimportant. One big use of NAND flash is in digital cameras for storage of photographs. Apple’s iPad, iPod, and iPhone also generate large demand for NAND flash as a way to store information to play back songs. In the future, NAND flash will likely be used to replace notebook hard drives. Samsung, Toshiba, SanDisk (joint venture with Toshiba), Micron, Hynix, Intel (joint venture with Micron), and Spansion are some companies that make NAND flash memory. Micron, Spansion, and Macronix are some companies that make NOR flash memory.

Other types of nonvolatile memory. These include electrically erasable programmable read-only memory (EEPROM) (pronounced E-squared PROM), erasable programmable read-only memory (EPROM), and read-only memory (ROM). None of these are very important today in terms of volume of sales, in our opinion.

Discrete Components

A discrete component is the most basic type of semiconductor device. A discrete component is a single elementary electronic device (such as a transistor). An integrated circuit (IC) is a chip in which many transistors and other devices (ranging from a few to more than a billion) are all connected together on a piece of silicon (a chip). Examples of discrete components include transistors and diodes. Discrete components are used for power management, voltage regulation, and to connect integrated circuits within a system board (i.e., printed circuit board). The discrete component market is approximately $18 billion in size (2013), or approximately 6% of the overall semiconductor market. For the four-year period 2003-07 (between the two downturns of the past decade), the discrete component market grew with a compound annual growth rate (CAGR) of 6%, versus an overall semiconductor CAGR of 11%. This trend continued into the 2007-09 period, with the discrete components market sliding 8%, versus a 6% decline for the semiconductor industry as a whole. Coming off the 2007-09 downturn, the discrete component market grew at a CAGR of 6% from 2009 to 2013, versus an overall semiconductor CAGR of 8%. We think, in general, the slower growth rate relative to the overall semiconductor market is in part the result of more chip designs including the functionality of discrete components in integrated circuits.

The discrete component market is highly fragmented, with no participant controlling more than 10% market share. Exhibit 31 highlights the top 25 participants in the discrete component market.


43

Exhibit 31. Discrete Market Share (2013)

Infineon Technologies, 8%

NXP, 7%

Toshiba, 6%

ON Semiconductor, 6%

Mitsubishi, 6%

STMicroelectronics, 6%

Renesas Electronics, 5%Vishay, 5%Fairchild Semiconductor, 5%Rohm, 5%International Rectifier, 4%Fuji Electric, 4%

Microsemi, 3%

Diodes, 3%

Freescale Semiconductor, 2%

Shindengen Electric, 2%

Panasonic, 2%

Denso, 1%

Toyota, 1%

Avago Technologies, 1%

Pan Jit, 1%

Sanken, 1%

IXYS, 1% Semtech, 1% Jilin Sino-Microelectronics, 1%

Others, 11%

Note: Chart created by Wells Fargo Securities, LLC (based on Gartner data) Source: Gartner, Inc., Market Share: Semiconductor Devices, Worldwide, 2013, Gerald Van Hoy et alia, March 31, 2014 Exhibit 32. Semiconductor Growth History By Chip Type (1990-2013)

CAGR 1990-

2000 CAGR 2000-

2003 CAGR 2003-

2007 CAGR 2007-

2009 CAGR 2009-

2013 Analog 15% (4%) 8% (6%) 6% Microprocessors 30% (5%) 6% (3%) 6% Microcontrollers, etc. 13% (25%) 9% (12%) 8% PLDs 29% (21%) 7% (4%) 9% Other Logic 12% 4% 15% (3%) 6% DRAM 16% (17%) 17% (15%) 12% Flash (NAND+NOR) 17% (7%) 11% Other Memory (ex. flash) 14% (41%) 2% (16%) (5%) Total IC 16% (8%) 12% (7%) 7% Total Discrete 9% (9%) 6% (8%) 6% Optoelec + Sensors 17% 10% 13% 2% 13% Total Semiconductor 15% (7%) 11% (6%) 8%

*Total flash growth is the combination of very strong NAND growth and declining NOR sales from 2003 through 2013. Source: Company reports, Semiconductor Industry Association, and Wells Fargo Securities, LLC estimates


44

Exhibit 32 shows historical growth by IC segment. We have broken out the past 23 years into five periods:

From 1990 to the beginning of 2000, ICs showed strong growth, with a CAGR of 16%, about 6 percentage points higher than unit growth of about 10% (though with a cyclical overlay.)

(1) The past 13 years have been affected two large downturns, in 2001 and 2009. In our view, the 2000-03, and 2007-09 growth numbers we have shown provide an interesting view into how the various segments of semiconductors fare through downturns. However, there are differences between the two periods. Communications-related chips were hit particularly hard in 2001 because of the communications infrastructure bubble in the late 1990s. The 2009 downturn was more of a broad-based downturn.

(2) Our long-term projection for IC sales and semiconductor sales in dollar terms is 10-12% per year, comparable to or slightly higher than underlying unit growth of 10% per year, which we think will continue. The 1990-2000 period benefited for a richening mix of chips. Overall growth from 2000 to 2011 was affected by the two downturns and also by falling ASP. However, IC ASP is currently (2014) running in the $1.20-1.30 range, similar to where it was in 1990. We believe that in the long run, ASP movements will be roughly neutral to semiconductor sales growth. Over the next few years, we think that growth in smartphones, tablets, and servers may help richen mix, driving up ASP.

(3) We think the period 2003-07 to be representative of a recent period of relatively “normal” growth.

1990-2000

As discussed in preceding sections, microprocessors grew strongly from 1990 to 2000 (30% per year CAGR), driven by the growth of the PC market.

Digital signal processors grew 36% per year from a small base, driven by a variety of end markets. The use of the DSP in wireless handsets was one driver of DSP growth during this period, we believe.

PLDs grew 29% per year, also from a small base. We think this was due to the emergence of PLDs as an alternative to custom chips (ASICs) for prototyping and specialized chips with relatively small run requirements. PLDs are used extensively in communications infrastructure and so, benefited from the communications boom toward the end of the 1990s.

Analog and DRAM both had growth roughly equal to the overall IC growth of 16% from 1990 to 2000 (though pricing movements resulted in DRAM growth jumping in the first half of the decade and then dropping back in the second half).

2000-03 (Downturn Followed By First Phases Of Recovery)

We believe that PLDs were hit particularly hard, declining with a negative 21% CAGR, because of the overbuilding of communications infrastructure toward the end of the 1990s.

DRAM declined at a substantial 17% CAGR, demonstrating how commodity-like segments are particularly sensitive. The large decline for DRAM through this period was in part the result of pricing compression being above normal trend and in part, a reduction in unit (bit) growth.

2003-07 (Period Of Normal Growth)

ICs as a whole grew 12% per year from 2003 to 2007, below the 16% per year growth from 1990 to 2000. As discussed, the data suggest that the underlying unit growth for the industry has changed much in the past 25 years, running at a CAGR of 10%. The higher revenue growth number for 1990-2000 was in part driven by rising ASPs, resulting from a mix shift related to PCs being a big driver of overall semiconductor growth. In the 2003-07 period, wireless handsets were an important high-growth semiconductor end market, which, in our view, did not provide quite as much of an opportunity for overall richening of mix that PCs did in the decade of the 1990s.

DRAM did well, with a CAGR of 17% per year from 2003 to 2007, but then declined more than semiconductors overall in the 2009 downturn (a decline of 15% per year CAGR in 2007-09), the effect being better-than-trend pricing from 2003 to 2007, followed by a pricing collapse in 2007-09. For periods of rapidly alternating upturns and downturns such as we have had from 2000 through 2009, we would expect DRAM to outperform in the upturns and underperform in the downturns because of pricing swings. For longer periods, such as 1990-2000, the long-term growth of DRAM roughly tracks the overall semiconductor market.


45

Nestled within the overall flash CAGR numbers shown in Exhibit 32 are strong growth numbers for NAND flash and declining sales for NOR flash. We do not have NAND data for 2003, but from 2004 through 2007, NAND flash sales grew at a CAGR of 31%.

Microprocessors underperformed with a 6% CAGR from 2003 to 2007. However, the primary end market for microprocessors, PCs, was strong during this period, and the microprocessor CAGR was pulled down by ASP contraction. We believe that this was driven in part by competition between Intel and AMD, and in part by a mix shift toward lower-end desktops and notebooks, partially offset by a positive mix shift of notebooks having higher growth than desktops (notebook microprocessors generally have higher ASPs than desktops).

There are a number of theoretical reasons as to why PLDs might have better secular growth opportunities than ICs in general. However, from 2000 to 2007, PLD growth was, in fact, below aggregate IC growth, declining with a CAGR of negative 21% per year from 2000 to 2003 and then growing only 7% per year from 2003 to 2007. We think that this may have been due in part to the need to grow into the considerable overcapacity in communications infrastructure that was created toward the end of the 1990s.

2007-09 (Downturn of 2008/2009)

As noted in the prior section, pricing declines drove down DRAM revenue in 2009, with the DRAM segment declining with a CAGR of 15% from 2007 to 2009.

NAND flash actually achieved a slightly positive CAGR, of 1% from 2007 through 2009. NAND was less than half of total flash sales in 2004 and grew to being more than three-quarters of the total flash market by 2009.

Microprocessor pricing was stable through the depths of the downturn in 2009, and microprocessor outperformed the overall semiconductor market from 2007 to 2009.

The PLD segment significantly underperformed the broader chip group in the downturn of 2000-03 because there was a large overbuild in one of the big PLD end markets (communications infrastructure). However, there was no similar PLD-specific issue in the 2007-09 downturn, and PLD declines in this period (a CAGR of negative 4%) were roughly the same as overall IC declines (a CAGR of negative 7%).

There are two opposing factors that affect analog in downturns:

o Analog pricing tends to be quite stable since much of the analog customer base is fragmented (few large customers to demand price concessions) and analog prices tend to be relatively low (average price of an analog chip close to $0.50, compared to about $1.30 ASP for ICs overall). This should make the analog segment more resilient in downturns. Indeed, it appears as if the profitability of analog companies does hold up very well in downturns. For example, Linear Technology, which does all its own wafer manufacturing, reported a gross margin of 77% in the June 2008 quarter (prior to the downturn, which gained momentum in December 2008), and lost just 3 percentage points of gross margin to report a 74% gross margin in the March 2009 quarter, the depths of the downturn.

o On the other hand, analog companies tend to sell a high percent of their product through distribution, and many analog companies recognize at least their international distribution revenue on sell-in to distribution. In a downturn, such companies are affected both by a reduction in end-market demand and also a reduction on inventory in distribution.

In the 2000-03 drop, analog sales fell, with a CAGR of only negative 4%, compared to a bigger CAGR drop rate of 8% of overall ICs. The corresponding recovery from 2003 to 2007 was, accordingly, more muted, with a CAGR of 8%, compared to IC’s growing at a CAGR of 12%. In the downturn of 2008 and 2009, analog declined with a CAGR of negative 6% from 2007 to 2009, close to ICs overall declining with a CAGR of negative 7%.

2009-2013 (recovery followed by three soft years). The year 2010 was one of strong recovery, followed by an inventory correction in the second half of 2011, a soft year for semiconductors in 2012, and a year of moderate growth in 2013. From 2009 to 2013:

Flash memory continued to show the strong secular growth of NAND, with total flash CAGR of 11%, driven by a 17% CAGR for NAND flash sales. However, NOR flash has been in secular decline, affected by wireless handsets moving away from using NOR flash.


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The DRAM CAGR of 12% was above total IC growth, driven by strong pricing dynamics in 2013. DRAM pricing has continued to be strong in 2014, leading to DRAM growth in that could well be close to 30% in 2014, resulting in a 2009-2014 CAGR of close to 10%. In our view, DRAM pricing is currently (November 2014) running at far above its equilibrium point, and we think that DRAM growth in recent years has been unsustainably high. There are several dynamics at play in the DRAM industry at the moment, including slowing bit growth demand, consolidation of DRAM providers, which could potentially help stabilize pricing, and a slowing rate of technology transitions. We believe that overall DRAM revenue growth might slow over the next few years, though it is possible that the profitability of the segment could remain solid.

PLD chips achieved a 9% CAGR, above overall IC growth of 7%. Altera and Xilinx have both suggested in the past that the PLD segment could be at a point at which secular PLD growth could begin to run above aggregate IC growth, with PLD’s eating into the broader custom chip application-specific integrated circuit (ASIC) market. The modest outperformance from 2009 to 2013 could be evidence of this, but we see it more as a reversal from underperformance in the years 2000-07. It appears that in 2014 PLD growth will match overall IC growth, with, we estimate, revenue for Altera+Xilinx, up 9%, compared to our expectation that IC growth might be of the order of 8-10% in 2014.

Despite investor concerns about the cannibalization of computers by mobile devices, microprocessors achieve a 6% CAGR from during this period, close to overall IC growth of 7%.

In the following sections we provide more detail on some of what we consider to be the more interesting semiconductor segments.

Sub-Segments of Interest

Microprocessors -- Some Microprocessor Concepts And Terms

What is a microprocessor (CPU)? A microprocessor is a logic chip that provides the thinking capability in a computer or other device. Another term often used for a microprocessor is a central processing unit (CPU). Microprocessors accounted for 16% of total IC sales in 2013. We discuss microprocessors in detail in our quarterly Processor Review.

Who makes microprocessors?

o x86 microprocessors

Intel is the world’s biggest maker of microprocessors. Most of the processors Intel makes are based on the x86 instruction set and are called x86 microprocessors.

AMD and VIA also make microprocessor based on the x86 instruction set. Intel owns the intellectual property and licenses the right to make x86 microprocessors to AMD and VIA. We believe that under the terms of the agreement Intel has with AMD, the license automatically renews periodically (Intel cannot decide to stop the license agreement). However, our understanding is that there is a change-of-control clause in the license, resulting in the termination of the license in the event of a change of control at AMD (another company cannot acquire AMD and obtain the right to make x86 processors through such an acquisition).

o ARM processors

ARM does not make microprocessors, but it does design microprocessor cores, which it licenses to various chip makers.

Qualcomm, Apple, Texas Instruments, Nvidia, and MediaTek are some companies that license ARM cores, which they include in their own microprocessor designs. ARM-based microprocessors are used extensively in smartphones and in tablets.

o PowerPC

IBM makes PowerPC processors. Apple used to use PowerPC in all its desktop and notebook computers, but switched to x86 processors from Intel in 2006. PowerPC is primarily used by IBM, itself, for its mainframe computers and its Unix servers.


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o Itanium

Intel makes Itanium processors for Unix servers used by companies like HP. HP also has server lines based on x86 microprocessors.

o SPARC

Oracle (Sun) makes SPARC processors, which it uses for its Unix server line. Oracle also has server lines based on x86 microprocessors.

o Other processors

There are a number of (relatively small) companies like MIPS and Tensilica that design processor cores, which they license to other chip companies.

The difference between processor chips and processor cores.

Chips. Almost all desktop and notebook computers contain a single microprocessor to do their thinking. Some servers contain just one processor chip and are called 1-way servers. Most servers have two processor chips and are called 2-way servers. Some servers have four chips or more.

Cores. A single processor chip contains several circuits on the same piece of silicon. The circuit on a processor that does the thinking is the processor core, but there are also other parts of the chip, like memory and other circuitry. Many microprocessors have multiple cores, many thinking circuits, each of which can think by itself. Most desktop and notebook computers used dual-core processors (2 cores on a processor). Higher end desktops have quad-core processors (4 cores on a processor). Sever microprocessors typically have more cores. Currently Intel offers server chips with up to 10 cores. Thus, a typical server might have several chips (e.g., two chips in a 2-way server) and each chip might have several cores. So a 2-way server that is populated with 6-core microprocessors actually has 12 little brains (2x6).

Microprocessor specifications and terms.

Clock frequency. Microprocessors are clocked chips, which means that all calculations or other operations in the circuit wait for a beat of a clock before they happen. This makes sure that signals are transferred at the same time, avoiding errors that may occur as a result of one thing happening earlier than something else. The higher the clock frequency, the more things that can happen per second and the more the chip can achieve. Typical clock frequencies for Intel processors are 1.0-3.5 GHz (Gigahertz), 1.0-3.5 billion clock cycles per second. Therefore, billions of things happen within a microprocessor each second. Higher frequencies in microprocessors thus allow processors to achieve more in a given amount of time, resulting in an improvement in microprocessor performance.

Cache memory. Microprocessors have a certain amount of memory included on the microprocessor chip, which is where information is temporarily stored while the microprocessor is working on the information. Microprocessor performance is typically improved by having more cache memory available. There are often as many as three layers of cache memory available: level 1, level 2, and level 3 (L1, L2, and L3 cache). For a processor with more than one core, the extent to which the cache is shared affects how much the cache helps performance. Cache memory that is shared among all the cores has more impact on performance than cache memory that is restricted in its use to a subset of cores. L1 cache is typically small and attached to a single core, while L2 and L3 cache is often shared. Today’s microprocessors often have several megabytes of cache memory. The cache memory is typically SRAM memory since SRAM circuitry can be made with a standard logic process used for microprocessors, whereas DRAM circuitry needs special processing.

Thermal design power (TDP). The peak power consumption of the microprocessor is often specified in terms of thermal design power, or TDP. TDP is, in fact, a specification of how much heat is generated by the microprocessor when it is running as hard as it can. It is the heat that a system needs to be designed to remove from the chip. For server processors AMD uses an alternative specification, average CPU power (ACP), with ACP generally being lower than TDP for any given chip since it is not the peak power consumed (which is what TDP specifies), but the average power.

Die size. This represents the size of a chip. The smaller the chip, the lower the cost of the chip since more chips can be printed on a silicon wafer.


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Chipsets. A microprocessor works with an additional chip or pair of chips, the chipset, which handle most of the communications between the microprocessor and the rest of the computer. We discuss what chipsets do in more detail further on in this report.

Integrated graphics versus discrete graphics. Computers use microprocessors for general purpose thinking, but as well as this, many applications need some additional circuitry to do computations related to displaying graphics on the computer screen. For many computers (one-half to three-quarters of desktops and notebooks), the graphics computations are dealt with by integrated graphics, which is circuitry that is included either with the chipset, or included with the microprocessor. For computer users that are prepared to pay extra, a separate graphics card is included with the computer that contains a stand-alone graphics chip and some memory. This is discrete graphics.

Tick-Tock (Intel). Intel has developed new microprocessors on what it calls a “Tick-Tock” schedule, introducing a new microprocessor product family each year on a two-year cycle as follows:

o Year 1, new manufacturing technology using existing microprocessor design. For example, this year (2014), Intel began to transition to its Broadwell product family. Broadwell processors have essentially the same circuit design as Haswell, but are manufactured on Intel’s 14nm manufacturing technology.

o Year 2, new microprocessor core design on an existing manufacturing technology. For example, next year (2015), we believe Intel will ramp its Skylake product family in the second half of the year. This family features a new processor design, manufactured on 14nm manufacturing technology.

Exhibit 33. Total ICs Versus Microprocessor (Year-Over-Year Growth)

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Exhibit 33 shows the growth of microprocessors compared with overall integrated circuits. As shown in Exhibit 32, microprocessors performed better than semiconductors as a whole from 1990 to 2003, and again from 2007 to 2009. Despite investor concerns about the cannibalization of computers by mobile devices, microprocessors achieved a 6% CAGR from 2009 to 2013, comparable to overall IC growth of 7%.

There are a number of different microprocessor architectures, but x86 processors account for the bulk of total microprocessor sales. Intel and AMD are the main makers of x86 microprocessors (see Exhibit 34).

Exhibit 34. Total x86 Microprocessor Market Share Over Time

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Intel (excl. tablet Atom, Phi, Itanium) AMD (excl semi custom) VIA

Source: Mercury Research and Wells Fargo Securities, LLC

Exhibit 34 shows that in H2 2005, Intel began losing microprocessor market share to AMD. AMD’s share gains were driven by some good design decisions on AMD’s part that gave AMD a performance lead in desktop and server processors. AMD also began to build out its notebook processor line, which further fueled its market-share gains. AMD’s market share peaked at about 25% in the December 2006 quarter from about 16% in the June 2005 quarter. However, in 2006, Intel managed to re-establish a clear performance leadership position in essentially every high-volume microprocessor segment with a series of new microprocessor families, which resulted in AMD’s overall processor market share falling steadily since the end of 2006 through to today (2014).

Microprocessors are among the highest-priced chips. Exhibit 35 shows the average microprocessor selling price as reported by Intel and AMD. Intel’s overall microprocessor ASP is about $140, with its highest-priced chips (top-end server microprocessors) commanding prices that stretch to several thousand dollars.


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Exhibit 35. Average Microprocessor Selling Price--Intel Versus AMD

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Intel (excl. Itanium, Phi, and tablet Atom) AMD (excl. semicustom)

Source: Mercury Research and Wells Fargo Securities, LLC estimates

Intel’s overall microprocessor ASP (around $140) is currently more than double AMD’s (around $60), due to a better mix of higher performance chips.

Microprocessor ASP was fairly stable from 2001 through 2005, though it fell between 2005 and 2008 for both Intel and AMD. Intel’s microprocessor ASP has for the most part been on an upward trend since early 2009, while AMD’s microprocessor ASP has drifted downward in this period, in part the result of AMD’s position eroding in the high ASP server processor market.

Exhibit 36 is a pricing table that shows an example of list prices posted on Intel’s and AMD’s websites. List prices are not necessarily the actual prices at which the microprocessor companies sell chips to large PC makers, but we think that list pricing is a helpful indicator of general pricing trends and the pricing positioning of Intel and AMD. We generally assume that the large customers get discounts to list prices of approximately 30%. However, we believe that it is difficult to get reliable information on the amount that chips are discounted. We think that changes in discounting sometimes result in ASP movements for Intel and AMD that are not reflected in list prices.


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Exhibit 36. Performance Desktop Processor Offerings--Intel Versus AMD (Example Of Waterfall Effect)

Intel CPU Price AMD CPU Price Core i7 (Haswell E - 22nm) X4 (Athlon 28nm) i7-5960X (20M 8C 3.50 GHz 140W) $999 860K (3.7GHz 4C 4MB L2 95W) i7-5930K (15M 6C 3.70 GHz 140W) $583 840 (3.1GHz 4C 4MB L2 65W) i7-5820K (15M 6C 3.60 GHz 140W) $389 X2 (Athlon 28nm) Core i7 (Haswell Refresh - 22nm) 450 (3.5GHz 2C 1MB L2 65W) i7-4790 (8M 4C 3.60 GHz 84W) $303 i7-4790S (8M 4C 3.20 GHz 65W) $303 A-Series (Kaveri 28nm) i7-4790T (8M 4C 2.70 GHz 45W) $303 A10-7850K (3.7GHz 4C 4MB L2 95W) $142 i7-4785T (8M 4C 2.20 GHz 35W) $303 A10 Pro-7850B (3.7GHz 4C-CPU 8C-GPU 4MB L2 95W) A10 Pro-7800B (3.5GHz 4C-CPU 8C-GPU 4MB L2 65W) Core i5 (Haswell Refresh - 22nm) A10-7800 (3.5GHz 4C 4MB L2 65W) $132 i5-4690 (6M 4C 3.50 GHz 84W) $213 A10-7700K (3.4GHz 4C 4MB L2 95W) $122 i5-4590 (6M 4C 3.30 GHz 84W) $192 A8 Pro-7600B (3.1GHz 4C-CPU 6C-GPU 4MB L2 65W) i5-4460 (6M 4C 3.20 GHz 84W) $182 A8-7600 (3.3GHz 4C 4MB L2 65W) $91 i5-4690S (6M 4C 3.20 GHz 65W) $213 A6-7400K (3.5GHz 2C 1MB L2 65W) $77 i5-4690T (6M 4C 2.50 GHz 45W) $213 A6 Pro-7400B (3.5GHz 2C-CPU 4C-GPU 1MB L2 65W) i5-4590S (6M 4C 3.00 GHz 65W) $192 A6 Pro-7350B (3.4GHz 2C-CPU 3C-GPU 1MB L2 65W) i5-4570S (6M 4C 2.90 GHz 65W) $192 A6 Pro-7300B (3.8GHz 1MB L2 65W) i5-4590T (6M 4C 2.00 GHz 35W) $192 A4-7300 (3.8GHz 2C 1M L2 65W) i5-4460S (6M 4C 2.90 GHz 35W) $182 i5-4460T (6M 4C 1.90 GHz 35W) $182 X4 (Athlon 32nm) 760K (3.8GHz 4C 4MB L2 100W) Core i3 (Haswell Refresh - 22nm) 750 (3.4GHz 4C 4MB L2 65W) i3-4370 (4M 2C 3.80 GHz 65W) $149 750K (3.4GHz 4C 4MB L2 100W) i3-4360T (4M 2C 3.20 GHz 35W) $138 740 (3.2GHz 4C 4MB L2 65W) i3-4360 (4M 2C 3.70 GHz 54W) $138 i3-4350 (4M 2C 3.60 GHz 54W) $138 X2 (Athlon 32nm) i3-4160T (3M 2C 3.10 GHz 35W) $117 370K (4.0GHz 2C 1MB L2 65W) i3-4160 (3M 2C 3.60 GHz 65W) $117 350 (3.5GHz 2C 1MB L2 65W) i3-4150 (3M 2C 3.50 GHz 54W) $117 340 (3.2GHz 2C 1MB L2 65W) i3-4350T (4M 2C 3.10 GHz 35W) $138 i3-4150T (3M 2C 3.00 GHz 35W) $117 FX Series (Vishera 32nm) 9590 (4.7GHz 8MB L2 8MB L3 220W) $220 Pentium (Haswell Refresh - 22nm) 9370 (4.4GHz 8MB L2 8MB L3 220W) $204 G3460 (3M 2C 3.50 GHz 65W) $86 8370E (3.3GHz 8C 2MB L2 8MB L3 95W) $194 G3450T (3M 2C 2.90 GHz 35W) $75 8370 (4.0GHz 8C 2MB L2 8MB L3 125W) $194 G3450 (3M 2C 3.40 GHz 53W) $75 8350 (4.2GHz 8C 1MB L2 8MB L3 125W) $173 G3440 (3M 2C 3.30 GHz 53W) $75 8320E (3.2GHz 8C 2MB L2 8MB L3 95W) $142 G3440T (3M 2C 2.80 GHz 35W) $75 8320 (4.0GHz 8C 1MB L2 8MB L3 125W) $142 G3250T (3M 2C 2.80 GHz 35W) $64 6350 (4.2GHz 6C 6MB L2 6MB L3 125W) $122 G3250 (3M 2C 3.20 GHz 65W) $64 6300 (4.1GHz 6C 6MB L2 8MB L3 95W) $101 G3240T (3M 2C 2.70 GHz 35W) $64 4350 (4.3GHz 4C 4MB L2 4MB L3 125W) $97 G3240 (3M 2C 3.10 GHz 53W) $64 4300 (4.0GHz 4C 4MB L2 4MB L3 95W) $97 Core i7 (Ivy Bridge-E - 22nm) FX Series (Zambezi 32nm) 4960X (15M 6C 3.60GHz 130W) $999 8150 (3.6GHz 8C 8MB L2 8MB L3 125W) $183 4930K (12M 6C 3.40GHz 130W) $583 8120 (3.1GHz 8C 8MB L2 8MB L3 125W) $153 4820K (10M 4C 3.70GHz 130W) $323 6200 (3.8GHz 6C 6MB L2 8MB L3 125W) $132 6100 (3.3GHz 6C 6MB L2 8MB L3 95W) $112 Core i7 (Crystal Well [Haswell] - 22nm) 4170 (4.2GHz QC 4MB L2 8MB L3 125W) $122 4770R (6M 4C 3.20GHz 65W) $358 4130 (3.8GHz QC 4MB L2 4MB L3 125W) $112 4100 (3.6GHz QC 4MB L2 8MB L3 95W) $101 Core i7 (Haswell - 22nm) 4770T (8M 4C 2.50GHz 45W) $303 A Series (Richland 32nm) 4770S (8M 4C 3.10GHz 65W) $303 A10-6800K (4.1GHz QC 4MB L2 100W) $122


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4770K (8M 4C 3.50GHz 84W) $339 A10-6790K (4.0GHz QC 4MB L2 100W) $122 4771 (8M 4C 3.50GHz 84W) $314 A10-6700T (2.5GHz QC 4MB L2 45W) $142 4770 (8M 4C 3.40GHz 84W) $303 A10-6700 (3.7GHz QC 4MB L2 65W) $142 4765T (8M 4C 2.00GHz 35W) $303 A8-6600K (3.9GHz QC 4MB L2 100W) $97 A8-6500T (2.1GHz QC 4MB L2 45W) $91 Core i5 (Crystal Well [Haswell] - 22nm) A8-6500 (3.5GHz QC 4MB L2 65W) $97 4670R (4M 4C 3.00GHz 65W) $276 A6-6400K (3.9GHz DC 1MB L2 65W) $62 4570R (4M 4C 2.70GHz 65W) $255 A4-6320 (3.9GHz DC 1MB L2 65W) $49 A4-6300 (3.7GHz DC 1MB L2 65W) $40 Core i5 (Haswell - 22nm) A4-4020 (3.2GHz DC 1MB L2 65W) $40 4670T (6M 4C 2.30GHz 45W) $213 A4-4000 (3.0GHz DC 1MB L2 65W) $40 4670S (6M 4C 3.10GHz 65W) $213 4670K (6M 4C 3.40GHz 84W) $242 Virgo (Trinity32nm) 4670 (6M 4C 3.40GHz 84W) $213 A10-5800K (3.8GHz QC 4MB 100W) $122 4570T (4M 2C 2.90GHz 35W) $192 A10-5700 (3.4GHz QC 4MB 65W) $122 4570S (6M 4C 2.90GHz 65W) $192 A8-5600K (3.6GHz QC 4MB 100W) $91 4570 (6M 4C 3.20GHz 84W) $192 A8-5500 (3.2GHz QC 4MB 65W) $91 4440S (6M 4C 2.80GHz 65W) $182 A6-5400K (3.6GHz DC 1MB 65W) $57 4440 (6M 4C 3.10GHz 84W) $182 A4-5300 (3.4GHz DC 1MB 65W) $47 4430S (6M 4C 2.70GHz 65W) $182 4430 (6M 4C 3.00GHz 84W) $182 Lynx (Fusion 32nm) A8-3870K (3.0GHz QC 4MB 100W) $91 Core i3 (Haswell - 22nm) A8-3850 (2.9GHz QC 4MB 100W) $87 4340 (4M 2C 3.60GHz 65W) $149 A8-3820 (2.5GHz QC 4MB 65W) $101 4330T (4M 2C 3.00GHz 35W) $138 A8-3800 (2.4/2.7GHz QC 4MB 65W) $91 4330 (4M 2C 3.50GHz 65W) $138 A6-3670K (2.7GHz QC 4MB 100W) $77 4130T (3M 2C 2.90GHz 35W) $122 A6-3650 (2.6GHz QC 4MB 100W) $77 4130 (3M 2C 3.40GHz 65W) $117 A6-3620 (2.2GHz QC 4MB) A6-3600 (2.1GHz QC 4MB 65W) $77 Pentium (Haswell - 22nm) A6-3500 (2.1GHz 3C 3MB 65W) $59 G3430 (3M 2C 3.30GHzv 65W) $86 A4-3420 (2.8GHz DC 1MB) G3420T (3M 2C 3.20GHz 35W) $75 A4-3400 (2.7GHz DC 1MB 65W) $40 G3420 (3M 2C 3.20GHz 65W) $75 A4-3300(2.5GHz DC 1MB 65W) $36 G3220 (3M 2C 3.00GHz 65W) $64 E2-3200(2.4GHz DC 1MB) G3220T (3M 2C 2.60GHz 35W) $64 Pentium (Bay Trail 22nm) X6 (Phenom II - 45nm) J2900 (2M 4C 2.67GHz 10W) $94 1100T (3.3GHz 6C 3M L2 6M L3 125W) $194 J2850 (2M 4C 2.4GHz 10W) $94 1090T BE (3.2GHz 6C 3M L2 6M L3 125W) $173 1075T (3.0GHz 6C 3M L2 6M L3 125W) $163 Core i7 (Ivy Bridge - 22nm) 1065T (2.9GHz 6C 3M L2 6M L3 95W) 3770T (8M 4C 2.5GHz 45W) $294 1055T (2.8GHz 6C 3M L2 6M L3 125W) $153 3770K (8M 4C 3.5GHz 77W) $332 1045T (2.7GHz 6C 3M L2 6M L3 125W) 3770S (8M 4C 3.1GHz 65W) $294 3770 (8M 4C 3.4GHz 77W) $294 X4 (Phenom II - 45nm) 980 BE (3.7GHz QC 2M L2 6M L3 125W) $163 Core i5 (Ivy Bridge - 22nm) 975 BE (3.6GHz QC 2M L2 6M L3 125W) $153 3570T (6M 4C 2.3GHz 45W) $205 970 BE (3.5GHz QC 2M L2 6M L3 125W $142 3570K (6M 4C 3.4GHz 77W) $225 965 BE(3.4GHz QC 2M L2 6M L3 125W) $81 3570 (6M 4C 3.4GHz 77W) $205 955 BE(3.2GHz QC 2M L2 6M L3 125W) $81 3570S (6M 4C 3.1GHz 65W) $205 910e (2.6GHz QC 8M) $143 3550S (6M 4C 3.0GHz 65W) $205 905e (2.5GHz QC 8M) $100 3550 (6M 4C 3.3GHz 77W) $205 850 (3.3GHz 2M L2 QC 95W) 3475S (6M 4C 2.9GHz 65W) $201 840 (3.2GHz QC 8M) $103 3470 (6M 4C 3.2GHz 77W) $184 3470T (3M 2C 2.9GHz 35W) $184 X4 (Athlon II - 45nm) 3470S (6M 4C 2.9GHz 65W) $184 651 (3.0GHz QC 4M 100W) $92 3340S (6M 4C 2.8GHz 65W) $182 645 (3.1GHz QC 2M 95W) $102 3340 (6M 4C 3.1GHz 77W) $182 641 (2.8GHz QC 4M 100W) $81


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3330S (6M 4C 2.7GHz 65W) $182 640 (3.0GHz QC 2M 95W) $98 3330 (6M 4C 3.0GHz 77W) $182 638 (2.7GHz QC 4M 65W) $81 3350P (6M 4C 3.1GHz 69W) $177 631 (2.6GHz QC 4M 100W) $79 620e (2.6GHz QC 2M 45W) Core i3 (Ivy Bridge - 22nm) 615e (2.5GHz QC 2M 45W) $133 3250T (3M 2C 3.0GHz 35W) $138 610e (2.4GHz QC 2M) $122 3250 (3M 2C 3.5GHz 55W) $138 605e (2.3GHZ QC 2M) $98 3245 (3M 2C 3.4GHz 55W) $134 3240T (3M 2C 2.9GHz 35W) $117 3240 (3M 2C 3.4GHz 55W) $117 3225 (3M 2C 3.3GHz 55W) $134 3220T (3M 2C 2.8GHz 35W) $117 3220 (3M 2C 3.4GHz 55W) $117 3210 (3M 2C 3.2GHz 55W) $117

EE = Extreme Edition; SC = Single-core; DC = Dual-core; TC = Triple-core; QC = Quad-core; M = Megabytes of cache (e.g. 2M = 2MB); LE = <65W TDP (value chip) Source: Intel, AMD, and Wells Fargo Securities, LLC


54

Microprocessor Technology Topics

x86 and other types of microprocessors and processor cores. There are a number of different types of microprocessors, but the x86 microprocessors made by Intel and AMD account for the bulk of the total microprocessor market.

o x86 processors. x86 microprocessors are the microprocessors used in essentially every desktop and laptop computer sold in the world today. They are also used in x86 servers and in some other relatively minor applications. x86 microprocessors are microprocessors that implement the x86 instruction set. An instruction set is the set of commands that a microprocessor can carry out, the language in which the microprocessor thinks. Intel owns the rights to the x86 technology and AMD (and Via) manufacture microprocessors under license from Intel. Although Intel owns the rights to the x86 license set and AMD can manufacture microprocessor only under license from Intel, there are apparently terms in the license agreement that Intel has with AMD that require Intel to periodically renew the license to AMD under reasonable terms. The name “x86” comes from the series of Intel processors that powered the early PCs, the 8086, followed by the 80286, 80386, 80486, etc.

o ARM processors. ARM Holdings is a semiconductor company that licenses processor cores, rather than making its own chips. Other semiconductor companies include the circuit designs from ARM in their own chips and pay ARM a royalty. ARM built its business around the concept that a processor design was needed that had low-power consumption, to serve markets in mobile electronics, where battery life is an important consideration. ARM processors have a particularly important presence in the wireless handset market, with chips like Samsung’s Exynos chip, Qualcomm’s Snapdragon chip, and Nvidia’s Tegra chips all using ARM processors.

Some companies, including Nvidia, Samsung, and Broadcom, use ARM’s circuit design in processor cores that they include together with other circuitry on their chips.

Other companies, for example Apple and Qualcomm, license the use of the structure of the microprocessor from ARM (i.e., the instruction set), but design their own circuits to implement this microprocessor structure.

o PowerPC. IBM manufactures PowerPC to use in its own server products. At some point in the past, Apple used PowerPC for all its computers, but several years ago, Apple switched to Intel’s x86 products.

o SPARC. Sun Microsystems (Oracle) uses SPARC chips in its servers, as does Fujitsu. However, with the decline of the Unix server market and the acquisition of Sun by Oracle, we expect SPARC chips to (continue to) fade over time.

o Itanium. Itanium is a microprocessor made by Intel used in Unix servers.

Number of processing cores in a microprocessor. Each microprocessor has at least one microprocessor core. The microprocessor core is the primary “brain” of the microprocessor. Over the years there has been a trend away from having one very big microprocessor core to having many smaller cores on a chip. Increasing the number of cores results in increased performance without increasing the maximum frequency of a chip. It turns out that raising the frequency of a chip drives up power consumption more than increasing the number of cores, and power consumption has become an increasingly important consideration for microprocessors over the past few years, even in computers like desktops and servers, which are not meant to be portable. Exhibit 37 shows how the number of cores has risen in Intel’s microprocessors over the past few years. For the most part, microprocessors with multiple cores have all the cores included on a single chip.


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Servers and server processors--4-way and 2-way servers. An x86 server (a server that uses x86 processors) can be designed to use one, two, four, or more processors. A server that uses two processors is called a 2-way server, and one that has four processors is a 4-way server. In addition to having multiple processors in a server, each processor can have multiple cores. For example, a 4-way server might be filled with 8-core processors, which would make a total of 4x8 = 32 processor cores in that particular server.

Power consumption--thermal design power (TDP). Microprocessors have to balance computing capability and the amount of power that the chip consumes because of cooling considerations (the more power a chip consumes, the more cooling has to be provided for the chip). Power consumption is typically specified as “TDP.” Desktop and server processors typically have TDP specifications of 65 watts to 100+ watts, whereas notebook processors typically have TDP specifications of 15 watts or lower and tablet processors extend to TDPs below 5W.

Exhibit 37. Number Of Cores On Intel’s Microprocessors FY2006 FY2007 FY2008 FY2009 FY2010 FY2011 FY2012 FY2013

First 4-core First Atom First 6-core 6-core <1% <1% <1%4-core <1% 3% 8% 14% 13% 19% 32% 43%2-core 28% 70% 79% 80% 81% 76% 62% 52%1-core 72% 27% 12% 3% 2%Atom <1% 3% 4% 5% 6% 4%

First 2-core First 4-coreFirst Atom

4-core <1% 1% 7% 6% 8% 6%2-core 47% 77% 73% 65% 65% 75% 81% 83%1-core 53% 23% 16% 11% 7% 3% 1%Atom 11% 23% 21% 16% 10% 11%

First 4-core First 6-core First 8-core

6-core or greater4-core 2% 37%2-core 38% 56% 16% 4%1-core 60% 7%

First 4-core First 6-core6-core or greater4-core 2% 37% 84% 96%2-core 38% 56% 16% 4%1-core 60% 7%

100% 100% 100%

Xeon DP (2-way)100% 100% 100% 100%

Xeon MP (4-way)

84% 96% 100%

Desktop (incl. Atom )

Mobile (incl. Atom )



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Applications Processors

Application processors are processors used as the brains to run applications in tablets and smartphones.

Exhibit 38 shows details for leading application processors.

Most applications processors (except those made by Intel) have processor cores that are based on ARM architecture.

o Qualcomm, Nvidia, Samsung, and Apple have ARM-based applications processors.

Qualcomm and Apple implement the ARM processor core in their own circuit design. Nvidia and Samsung use circuit designs which they licensed from ARM.

o Intel makes applications processors using its own x86 architecture.

Qualcomm, Mediatek, Intel, and Nvidia are merchant chip companies that design processors which are used in tablets and smartphones made by other companies.

Apple designs its own applications processors and has these manufactured at a foundry (currently TSMC and Samsung). Apple’s applications processors are used solely in Apple’s own products, primarily iPad and iPhone.

Samsung’s processors are manufactured by Samsung’s semiconductor division, which operates separately from Samsung’s smartphone and tablet businesses. In principle, we believe that these chips are available for sale to any tablet or smartphone manufacturer, but we believe that in practice, Samsung’s tablet and smartphone processor are used primarily in Samsung devices. However, Samsung’s systems divisions also offer smartphones and tablets that use processors from other companies.

Exhibit 38. The Major Applications Processors

Company Family Intro Die Size (mm2)

Details

Intel

Follow-on from SoFIA

2016E 14nm integrated LTE/Processor manufactured internally at Intel.

Broxton (Willow Trail)

2015E 14nm Atom Goldmont, converged cores for tablets and smartphones. 64-bit.

SoFIA 4Q14E For low end tablets and for smartphones. Integrated global 3G HSPA+, connectivity with Intel Atom. Manufactured at an external foundry. Integrated LTE expected in 1H15. Quad core with integrated LTE for Rockchip 1H15, we expect there will also be customized SoFIA chips for Spreadtrum in 2015.

Broadwell Y 2H2014

14nm, high end notebook-class Core series processor cores, TDP low enough for fanless tablets. 64-bit.

Cherry Trail 2H2014E or early 2015E

14nm Atom Airmont, next generation graphics. 64-bit.

Moorefield 2H2014E Quad core 22nm Silvermont. 64-bit.

Merrifield Jan 2014 Dual core 22nm Silvermont. 64-bit.

Bay Trail 2H2013 ~100 22nm, 3D transistor, out of order Silvermont Atom x86 core, Intel Gen 7 Ivy Bridge graphics, 64-bit.

Ivy Bridge Y, Haswell Y

1H2013 2H2013 94, 177

22nm, 3D transistor, high end notebook-class Core series


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processor cores, 64-bit.

Clover Trail, Clover Trail+

2H2012 1H2013

96 32nm, dual core in-order Saltwell Atom x86 core, Imagination PowerVR graphics, 64-bit.

Medfield 1H 2012 63 32nm, single core Saltwell Atom x86 core, 64-bit.

Oak Trail 2011 65 45nm, single core, Bonnell Atom x86 core, 64-bit.

Qualcomm

Snapdragon 810/808

2H2014E (sample), 2H2014/1H2015E (production)

20nm, 64-bit, Hexa-core Cortex-A57 (2) with Cortex-A53 (4), Adreno 430/418, integrated CAT 6 LTE-A

Snapdragon 800/600/400

1H 2013 118 28nm HPm TSMC, quad/dual Krait (proprietary ARM) core, Adreno 3xx graphics, integrated baseband. 8-core 64-bit 600 series chip announced in Feb 2014, expected to sample in 3Q2014

Snapdragon 200

1H 2013 28nm LP TSMC, quad core ARM Cortex-A5 processor, Adreno 203 graphics, integrated baseband

MSM8960 2012 88 28nm TSMC, dual/quad core Krait processor, integrated baseband. Qualcomm also offers APQ series products which are standalone processors without integrated basebands

MSM8660 105 45nm TSMC, dual core Scorpion processor, integrated baseband.

Nvidia

Tegra K1 1H2014 (32-bit) 2H2014 (64-bit)

32-bit quad-core, 4-Plus-1 ARM Cortex A15 CPU and Nvidia-designed 64-bit dual Super Core CPU (Denver). Kepler GPU.

Tegra 4i 1H2013 28nm HPM, quad core Cortex A9 processor, GeForce graphics, integrated Icera software baseband

Tegra 4 1H 2013 ~80 28nm HPL, quad core Cortex A15 processor (with companion core), GeForce graphics

Tegra 3 2012 82 40nm TSMC, quad core Cortex A9 processor (with fifth control core), GeForce graphics

Tegra 2 2010 50 40nm TSMC, dual core Cortex A9 processor, ARM v11, Windows CE and Windows Mobile support, GeForce graphics

Tegra 2008 65nm TSMC, ARM11 Core

Samsung

Exynos 1H15E 14nm FinFET (with, we believe, 20nm metallization)

Exynos ModAP

Currently in planning, and only available as custom ASIC for specific customers

Integrated LTE Modem-AP solution. Capable to support 4G LTE Release 9 and Cat 4, at FDD and TDD, in addition to legacy 2G and 3G mobile interfaces

Exynos 5 1H 2013 28nm HKMG quad core Cortex A15 processor/Cortex A7 big.little (Octa variant with Imagination graphics) or 32nm Samsung, dual core Cortex A15


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processor with ARM Mali graphics.

Exynos 4 2011 120 45nm Samsung (newer 32nm version also), dual core Cortex A9 processor with ARM Mali graphics

Apple

A8 3Q2014 89 20nm technology, which we believe is manufactured at TSMC.

A7 2H 2013 102 28nm Samsung, Proprietary Apple/ARM processor, 64-bit architecture.

A6X 2012 124 32nm HKMG, dual core Swift (proprietary Apple/ARM) processor, quad core Imagination graphics 14.8mm2 CPU area, 35.4mm2 GPU area, 16 other digital blocks

A6 2012 96.5 32nm HKMG, dual core Swift (proprietary Apple/ARM) processor, tri core Imagination graphics, 14.9mm2 CPU area, 16.8mm2 GPU area, 17 other digital blocks

A5X 2012 165 45nm Samsung, dual core Cortex A9 processor, quad core Imagination graphics, 10.2mm2 32nm equivalent CPU area, 25.3mm2 32nm equivalent GPU area, 15 other digital blocks

A5_3 (TV) 2013 38 32nm Samsung, 4mm2 CPU area, 4.8mm2 GPU area, 9 other digital blocks

A5_2 (Ipad Mini, iPod, TV)

2012 71 32nm Samsung, dual core Cortex A9 processor, 10.6mm2 CPU area, 8.3mm2 GPU area, 12 other digital blocks

A5 2011 123 45nm Samsung, dual core Cortex A9 processor,, 9.9mm2 32nm equivalent CPU area, 9.8mm2 32nm equivalent GPU area, 12 other digital blocks

A4 2010 53 45nm Samsung, single core Cortex A8 processor,, 4.7mm2 32nm equivalent CPU area, 3.1mm2 GPU 32nm equivalent area, 9 other digital blocks

Source: Company Reports and Websites, Chipworks, Anandtech, Wells Fargo Securities, LLC.


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Tablet Processor Market. Exhibit 39 shows Strategy Analytics’ estimates of worldwide tablet processor market share in 2013 and estimates for H1 2014.

Strategy Analytics estimates that in Q2 2014, the tablet applications processor market grew 27% year over year, to $945 million, with units rising 23% year over year, to 65 million units.

In the June 2014 quarter, Apple maintained its lead with 22% unit share in the tablet applications processor market, with its A-series processors being the captive chips used in iPad. However, Apple’s share was down from 25% in Q1 2014 and 30% for the full year 2013.

o We expect Apple’s share of the overall tablet processor share will continue to drop as Android and Windows tablets ramp up in volume.

Intel’s share rose sharply, to 15% in Q2 2014 from 9% in Q1 2014 and 5% in 2013. The Strategy Analytics

numbers suggest that in the June 2014 quarter, Intel became the largest merchant chip supplier of tablet processors, behind Apple, which makes tablet chips only for its own use.

Qualcomm’s unit share was flat sequentially at 12% in Q2 2014; however, this was an increase from 8% in

2013. Amazon switched from using TI to using Qualcomm’s processors in its Amazon Kindle Fire tablet, and Qualcomm also appears to be establishing a foothold in some of Samsung’s tablets.

MediaTek’s share was also flat at 12% in Q2 2014, but was up from 8% in 2013, in part, we think, because

of ramping sales in tablets made and sold in China and elsewhere in Asia, both with Tier 1 tablet makers such as Lenovo, as well as smaller tablet makers.

Rockchip’s share of 5% in the total global tablet market, with its business concentrated in Chinese tablets,

implies a strong market position in China. Samsung’s share declined slightly, to 4% in Q2 2014 from 5% in Q1 2014 and 9% in 2013. Samsung uses its

Exynos processors in many of its own tablets, though it also uses processors from other chip vendors in some tablets.

Nvidia’s share was flat, at around 4% in Q2 2014, with no change from 2013 and down from 12% in 2012.

o Nvidia has said that it no longer considers the mainstream smartphone processor market to be a good target for its Tegra processor. We wonder if Nvidia will be able to maintain an appropriate level of tablet and smartphone business to support the investment needed to keep its processors competitive in the tablet space.

Exhibit 39. Total Tablet Unit Market Share

2Q14 Rank Vendor

2Q14 Units (M)

1Q14 Units (M)

2Q13 Units (M)

2013 Units (M)

2Q14 Share

1Q14 Share

2Q13 Share

2013 Share

1 Apple 14.4 13.5 14.4 72.5 22% 25% 27% 30% 2 Intel 9.8 4.9 2.6 11.3 15% 9% 5% 5% 3 MediaTek 8.1 6.4 4.3 19.8 12% 12% 8% 8% 4 Qualcomm 8.0 6.7 3.1 18.3 12% 12% 6% 8% 5 Allwinner 5.8 5.5 5.9 25.6 9% 10% 11% 11% 6 Rockchip 3.5 3.4 3.3 13.9 5% 6% 6% 6% 7 Marvell 3.5 2.9 2.8 13.5 5% 5% 5% 6% 8 Samsung 2.8 2.5 5.0 20.9 4% 5% 9% 9% 9 Nvidia 2.4 2.1 1.9 8.8 4% 4% 4% 4%

10 Amlogic 1.3 1.2 1.6 6.2 2% 2% 3% 3%

Others 5.4 4.9 8.2 30.2 8% 9% 15% 13%

Total 64.9 54.1 53.0 241.1 100% 100% 100% 100% Source: Strategy Analytics, Wells Fargo Securities, LLC estimates.


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Smartphone Processor Market. As shown in Exhibit 40, Strategy Analytics estimates show that in Q2 2014, the smartphone applications processor market grew about 20% sequentially and 22% year over year, to $5.2 billion, while unit shipments increased approximately 17% sequentially and 25% year over year, to 364 million units.

For Q2 2014, Qualcomm expanded its share of the smartphone apps processor market with a 41% unit share, up from 37% in Q1 2014 and 34% in 2013, followed by MediaTek, with 24% share, and Apple, with 12% share.

Strategy Analytics estimates that Samsung’s smartphone applications processor shipments continued to decrease, falling 20% sequentially and 49% year over year in Q2 2014, implying a shift by Samsung away from use of its own Exynos processors in its smartphones.

Nvidia’s smartphone processor shares remains low, at about 1% in Q2 2014, Q1 2014, and for full year 2013.

o Nvidia has said that it no longer considers the mainstream smartphone market is a particularly good market for Tegra, though it implied it still has an interest in the “super phone” market. We would not be surprised if Nvidia eventually exited the phone processor market altogether.

The Strategy Analytics numbers suggest that Intel continues to have a very small position in the smartphone market.

o Intel’s lack of an integrated baseband-processor product appears to be limiting its ability to penetrate the smartphone processor market. We do not expect Intel to gain any significant share in the smartphone processor market until perhaps 2015 at the earliest, with the launch of its SoFIA product in late 2014.

The numbers we have compiled are for stand-alone and integrated applications processors combined.

o The numbers shown for Apple, Samsung, and Intel are primarily stand-alone processors. We believe that Apple iPhone and Samsung Galaxy account for the majority of stand-alone processor use.

o The numbers shown for MediaTek, Spreadtrum, and Broadcom are primarily for integrated processors (and hence, overlap with the baseband unit data we discuss in the next section).

o Strategy Analytics estimates that about 10-15% of Qualcomm’s applications processor shipments are stand-alone processors and 85-90%, integrated processors.

Apple’s smartphone processor shipments are all discrete processors (Apple’s A8, A7, etc.) used in Apple iPhones, as are Samsung’s (Samsung’s Exynos processors). However, the units shipped by most of the other major vendors are, we believe, for the most part integrated modem/processor chips or chipsets. Therefore, the unit numbers included in Exhibit 40 are to some extent duplicated in the modem data we present in the next section.

Exhibit 40. Total Smartphone Processor Unit Market Share

2Q14 Rank Vendor

2Q14 Units (M)

1Q14 Units (M)

2Q13 Units (M)

2013 Units (M)

2Q14 Share

1Q14 Share

2Q13 Share

2013 Share

1 Qualcomm 150.9 115.7 103.6 397.6 41% 37% 36% 34% 2 MediaTek 85.8 76.5 53.7 219.9 24% 25% 18% 19% 3 Apple 45.4 35.9 34.5 162.9 12% 12% 12% 14% 4 Spreadtrum 35.8 30.1 45.8 144.2 10% 10% 16% 12% 5 Marvell 15.6 13.4 10.0 38.3 4% 4% 3% 3% 6 Broadcom 9.6 17.2 15.5 77.9 3% 6% 5% 7% 7 Samsung 9.6 11.9 18.6 73.0 3% 4% 6% 6% 8 HiSilicon 3.1 3.0 2.1 7.5 1% 1% 1% 1% 9 NVIDIA 2.9 3.0 0.5 6.6 1% 1% 0.2% 1%

10 Intel 1.6 1.0 0.7 2.2 0.4% 0.3% 0.3% 0.2% Others 4.1 4.0 5.6 26.9 1% 1% 2% 2% Total 364.2 311.6 290.5 1156.9 100% 100% 100% 100%

Source: Strategy Analytics, Wells Fargo Securities, LLC estimates.


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Basebands. Baseband processors (modems) are the primary communication chip for both voice and data in a smartphones. Some tablets also have baseband modules for long-range communications, though many tablets are offered with just short-range communications chips (WiFi).

Exhibit 41, Exhibit 42, and Exhibit 43 show baseband unit market share for 2013 and H1 2014 for the overall cellphone market, the 3G (3rd generation) market and the 4G market, respectively. Originally wireless handsets were used for voice communications. At the 3G level, the communications standard became capable of supporting reasonably good data transmission, as well, and so smartphones, which have a fair amount of computing capability in addition to supporting voice communications, tend to have at least 3G communications capability. More recently, various regions of the world have been building out 4G networks, which work on the long term evolution (LTE) standard.

According to Strategy Analytics estimates, total baseband shipments increased 5% sequentially and 6% year over year in the June quarter; 3G baseband shipments increased 6% sequentially and 8% year over year; and LTE baseband shipments increased 28% sequentially and 98% year over year. Strategy Analytics estimates that Qualcomm captured 94% unit share in the LTE baseband market in H1 2013.

Qualcomm continues to dominate the baseband market, with its overall blended share rising to 39% in Q2 2014 (from 34% for Q1 2014 and 32% for full-year 2013), and its 3G share rising to 46% (from 42% in Q1 2014 and 45% for full-year 2013); however, its LTE share was flat sequentially at 85% and down from 93% share for full-year 2013.

Strategy Analytics estimates that Marvell’s LTE shipments jumped 34% sequentially, to 5.4 million units in Q2 2014, an impressive jump from 0.7 million units for the full year 2013.

o Strategy Analytics is projecting Marvell’s LTE shipments might decline to 4.4 million units in Q3 2014.

Strategy Analytics estimates that Intel shipped 3.3 million LTE units in the June quarter (up 27% sequentially).

Strategy Analytics estimates MediaTek shipped 1.3 million LTE units in the June quarter, though it estimates MediaTek’s 3G market share jumped to 27% in the June 2014 quarter, up from 18% for the full year 2013 (flat sequentially).

In Q2 2014, Broadcom announced that it had decided to proceed with closing down its baseband business.


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Exhibit 41. Total Baseband Unit Market Share

2Q14 Rank Vendor

2Q14 Units (M)

1Q14 Units (M)

2Q13 Units (M)

2013 Units (M)

2Q14 Share

1Q14 Share

2Q13 Share

2013 Share

1 Qualcomm 224.1 187.0 172.7 747.8 39% 34% 32% 32% 2 MediaTek 158.8 158.1 121.7 569.0 27% 29% 22% 24% 3 Spreadtrum 91.2 82.5 87.7 346.0 16% 15% 16% 15% 4 Intel 41.6 50.9 74.6 335.2 7% 9% 14% 14% 5 Marvell 19.6 17.0 11.0 50.5 3% 3% 2% 2% 6 RDA 15.9 20.2 38.5 138.8 3% 4% 7% 6% 7 Broadcom 9.6 17.3 16.4 79.9 2% 3% 3% 3% 8 VIA 5.1 5.0 5.0 20.9 1% 1% 1% 1% 9 HiSilicon 3.9 3.0 0.1 3.6 1% 1% 0% 0%

10 Samsung 2.9 2.5 2.5 10.7 0% 0% 0% 0% Others 7.1 7.6 16.5 70.4 1% 1% 3% 3% Total 579.9 551.0 546.7 2372.8 100% 100% 100% 100%

Source: Strategy Analytics, Wells Fargo Securities, LLC estimates Exhibit 42. UMTS/CDMA/W-CDMA/TD-SCDMA (3G) Baseband Unit Market Share

2Q14 Rank Vendor

2Q14 Units (M)

1Q14 Units (M)

2Q13 Units (M)

2013 Units (M)

2Q14 Share

1Q14 Share

2Q13 Share

2013 Share

1 Qualcomm 119.5 104.8 113.4 445.8 46% 42% 47% 45% 2 MediaTek 70.9 66.6 40.1 175.3 27% 27% 17% 18% 3 Spreadtrum 28.0 23.6 28.4 99.4 11% 10% 12% 10% 4 Marvell 14.1 12.8 10.6 48.1 5% 5% 4% 5% 5 Intel 9.8 13.7 22.4 88.7 4% 6% 9% 9% 6 Broadcom 9.1 16.3 15.8 78.6 3% 7% 7% 8% 7 VIA 5.1 5.0 5.0 20.9 2% 2% 2% 2% 8 HiSilicon 1.3 1.1 0.1 2.2 0% 0% 0% 0% 9 ST-Ericsson 0.6 0.6 4.3 19.4 0% 0% 2% 2%

10 RDA 0.4 - - - 0% 0% 0% 0% Others 3.5 3.4 2.6 12.9 1% 1% 1% 1% Total 262.4 247.9 242.8 991.2 100% 100% 100% 100%

Source: Strategy Analytics, Wells Fargo Securities, LLC estimates Exhibit 43. LTE Baseband Unit Market Share

2Q14 Rank Vendor

2Q14 Units (M)

1Q14 Units (M)

2Q13 Units (M)

2013 Units (M)

2Q14 Share

1Q14 Share

2Q13 Share

2013 Share

1 Qualcomm 103.4 81.0 57.6 296.4 85% 85% 94% 93% 2 Marvell 5.4 4.0 - 0.7 4% 4% 0% 0% 3 Intel 3.3 2.6 0.1 3.2 3% 3% 0% 1% 4 Samsung 2.9 2.5 2.5 10.7 2% 3% 4% 3% 5 HiSilicon 2.6 1.9 0.0 1.4 2% 2% 0% 0% 6 MediaTek 1.3 - - - 1% 0% 0% 0% 7 Altair 0.6 0.6 0.0 1.0 1% 1% 0% 0% 8 GCT 0.5 0.4 0.6 2.4 0% 0% 1% 1% 9 Broadcom 0.4 0.9 - 0.0 0% 1% 0% 0%

10 Sequans 0.4 0.3 0.0 0.2 0% 0% 0% 0% Others 0.6 0.5 0.4 1.0 0% 1% 1% 0% Total 121.4 94.7 61.3 317.1 100% 100% 100% 100%

Source: Strategy Analytics, Wells Fargo Securities, LLC


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Discrete Graphics Chips

Although the microprocessor makers provide graphics circuitry with their microprocessor products (integrated graphics), there is also a fairly large market for separate chips that just do graphics: discrete graphics processor units (GPU). Nvidia and AMD are the primary makers of GPUs (see Exhibit 44). AMD’s discrete graphics product line (and the company’s integrated graphics expertise) comes from its acquisition of ATI in 2006. AMD still uses the ATI brand for its discrete graphics products.

Exhibit 44. Discrete Graphics Chip--Market-Share Trends

0%

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Q1 08

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Discrete GPU M

arket Share

Nvidia AMD/ATI

Source: Mercury Research and Wells Fargo Securities, LLC The bulk of GPUs are used in desktop and notebook computers. Exhibit 45 shows an attached rate of GPUs to microprocessors, our estimate of the proportion of microprocessors that are used together with a GPU in a system.

Our graphs suggest that historically, some 30-40% of desktops, workstations, and servers, and about 25-30% of notebooks feature discrete GPUs. Most microprocessors are sold with integrated graphics. Therefore, the proportion of systems that contain both integrated graphics and discrete graphics is fair.

We think that one risk to the attach rate of GPUs is the recent action by Intel and AMD to bring graphics circuitry onto the microprocessor chip. Prior to 2011, integrated graphics circuitry was part of the chipset. Integrated graphics circuitry that is included on the microprocessor chip benefits from having access to the memory included on the microprocessor chip and direct communications with the microprocessor without the delays associated with driving signals from chip to chip. Intel has made the claim that its integrated graphics performance is now equal to some GPUs. AMD already has significant graphics expertise from its GPU product lines, and our understanding is that AMD is using similar circuitry in its integrated graphics to what it has in its GPUs. If Intel and AMD truly do close the performance gap between integrated graphics and GPUs, this could well result in a falling attach rate for GPUs in the future.

While driving graphics performance for PCs is the single biggest application for GPU chips, other applications include graphics for workstations, i.e., improving the performance applications like computer-aided design (CAD). Since graphics processing is very computationally intensive, GPUs have a great deal of mathematical computation capability. One application for GPUs that Nvidia is promoting is coprocessors in high-performance computing.


64

Exhibit 45. Discrete Graphics Chip--Attach Rate

0%

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Q1 08

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Discrete GPU Shipments As A Percen

tage

Of

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ipments

Desktop/Workstation/Server Notebook Excl. Tablets



65

Memory

There are two main types of semiconductor memory:

(1) Volatile memory. This memory forgets what it is supposed to be remembering when the power is switched off. The main type of volatile memory is DRAM.

(2) Non-volatile memory. This memory recalls what it is supposed to be remembering even when the power is switched off. The main type of nonvolatile memory is flash memory, which itself is divided into NAND flash and NOR flash.

Exhibit 46. Memory Segment Breakout (2005 Through 2013)

DRAM53%

NOR Flash16%

NAND Flash22%

Other Memory9%

2005 Memory Share

DRAM50%

NOR Flash10%

NAND Flash33%

Other Memory

7%

2009 Memory Share

DRAM52%

NOR Flash3%

NAND Flash41%

Other Memory

4%

2013 Memory Share

Source for all charts: Semiconductor Industry Association and Wells Fargo Securities, LLC Exhibit 46 shows that DRAM is the largest component of the memory market, accounting for 52% of the total memory market. Over the past few years, NAND Flash sales have ramped more quickly than the other memory segments, climbing to 41% of the overall memory market in 2013 from 22% in 2005. NAND flash has probably cannibalized NOR flash to some extent, while also serving new markets.

DRAM

There are two main types of volatile memory:

(1) DRAM. DRAM (or dynamic RAM) forgets what it is supposed to be remembering even when the power is switched on, and so it needs to constantly remind itself of what it has been told (refresh) several hundred times per second.

(2) SRAM. SRAM (or static RAM) remembers what it has been told as long as the power stays on.

DRAM is less expensive than SRAM and can be made in higher densities. Since the DRAM market is more than 10x the size of the SRAM market, we address only DRAM in this report.

DRAM is random access memory (RAM). This means that the information can be retrieved from any memory cell without looking through all the other memory cells. DRAM and SRAM are random access. NOR flash is random access, but NAND flash is serial access. For a NAND flash memory, all the cells in a whole line (a row) must be looked at one after the other.

DRAM is used as the main type of temporary silicon memory in computers that the microprocessors use when they are actively working. DRAM chips are usually described in terms of bits (the total number of digits that


66

can be stored, with each digit being either 1, or o), whereas computer memory is described in terms of bytes. There are 8 bits in a byte. A typical PC (e.g. a consumer laptop) might have 8 GB of DRAM. 8GB = 8 Gigabytes = 8 billion bytes. A 4 Gb chip costs about $3.00-$4.00 today (late 2014). Therefore, a typical PC might contain about $64 worth of DRAM chips in it, i.e., 16 chips of with 4 Gb of memory on each chip, or 32 chips with 2 Gb of memory each.

DRAM is used in other electronic devices, too, including wireless handsets, networking systems, and communications infrastructure systems. However, we estimate that more than half of the world’s DRAM consumption is for computers.

Exhibit 47 shows the main DRAM makers. Samsung is the world’s largest DRAM vendor (and is also a significant producer of flash memory), producing 36% of the world’s DRAM in 2013 (down from its 41% share in 2012). In our opinion, Samsung is also a leader in DRAM manufacturing technology. In 2013, Hynix held second place, with a 27% share, while Micron held third place with 22% share, followed by Elpida, in fourth place, with a 7% share. However, Elpida filed for bankruptcy in February 2012, after which Micron acquired the company, completing the transaction in 2013. Micron, with its Elpida acquisition, is now of comparable size to Hynix in DRAM.

Exhibit 47. DRAM Market Share (2013)

Samsung Electronics36%

SK Hynix27%

Micron Technology22% Elpida Memory

7%

Nanya Technology4%

Winbond Electronics1%

Others, <1% share, Includes Toshiba, Spansion, Fujitsu,

Rohm, Etron, Powerchip

3%

DRAM Market 2013 (Revenue)Total Market $34.9 billion

Note: Chart created by Wells Fargo Securities, LLC (based on Gartner data) Source: Gartner, Inc., Market Share: Semiconductor Devices, Worldwide, 2013, Gerald Van Hoy et alia, March 31, 2014

The semiconductor memory business is highly capital-intensive, but still commodity-like, and for this reason, we think memory has historically had bigger cyclical swings than the rest of semiconductors (see Exhibit 48 and Exhibit 54). When the business environment is weak, DRAM pricing tends to fall, and when business is strong, DRAM pricing rises. We think that these big swings in business, coupled with the capital intensity of the DRAM business, make it difficult for most DRAM companies to achieve consistent value accumulation over the long run. In recent years there has been a fair amount of consolidation in the memory industry, most recently with the acquisition of Elpida by Micron. We think it is possible that as the number of major DRAM makers shrinks and the growth of the market slows, pricing dynamics might stabilize.


67

Exhibit 48. DRAM And IC Revenue (Year-Over-Year Growth)

(100%)

(50%)

0%

50%

100%

150%

200%D

ec-9

1

Dec

-92

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Gro

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Total ICs DRAM

Source: Semiconductor Industry Association and Wells Fargo Securities, LLC Exhibit 49. DRAM Megabits Shipped

100,000

1,000,000

10,000,000

100,000,000

1,000,000,000

10,000,000,000

Dec

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tal D

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M M

bit

s 0

00s

DRAM Mbits 77%/yr (1990-2002) 53%/yr 2002 onward

Source: Semiconductor Industry Association and Wells Fargo Securities, LLC DRAM bit growth averaged around 77% per year from 1990 to 2001 and has been around 53% per year from 2001 through H1 2014. Our graph shows lower bit growth than 53% per year from H2 2012 to the present (H2 2014), it is unclear to us at the moment whether this further slowing is temporary or a secular step down.

These bit growth numbers are far higher than the unit growth rates of the electronic systems such as computers that DRAM sells into. DRAM growth is driven not just by growth of system units shipped, but also by the ever increasing amount of DRAM in the system. However, the number of DRAM chips in the system does not typically increase with time. Instead, it is the number of bits on each DRAM chip that increases.

The commodity-like nature of DRAM might be expected to increase the price elasticity of the demand for the product. However, Exhibit 49 shows that, historically, DRAM bit growth has been very consistent, with far less variation than shown in the DRAM revenue graph of Exhibit 48.


68

Exhibit 50 shows how DRAM price per bit has dropped over time. We have plotted price per bit, calculated from total DRAM sales divided by total bit shipments. This aggregates DRAM prices over many different densities of chips (i.e., today the average price per bit is calculated from sales of several different sizes of memory: 2 Gb, 1 Gb, 512 MB, 256 MB, 128 MB, etc.). Lower density chips tend to have a higher price per bit than the higher-density chips (there is less demand and hence, less pricing elasticity for older, legacy chips, and for these chips, the somewhat fixed packaging and test costs are a higher proportion of total chip cost). And so, the data of this graph often reflects a price per bit that is higher than the price per bit of the high-density volume runner at any given time.

It can be seen that actual price per bit can deviate significantly from the longer-term trend, but invariably, seems to return to the trend line. Our trend line shows that over the past two and a half years, DRAM price per bit has been moving sideways. As we discuss below, it is very possible that price per bit might not be declining as rapidly as it used to. However, we think that some investors have the unrealistic view that DRAM bit costs, and hence, the price per bit trend, may have stopped going down altogether. We expect that in time, DRAM prices will likely correct downward toward the longer term trend line.

We think the reason is that the trend line, in fact, approximates the cost per bit of making DRAM. Over time, transitions to smaller line widths allow memory makers to reduce the size of each memory cell, packing more memory (more bits) into the same silicon area. Since manufacturing cost is proportional to silicon area used, this reduces price per bit. We think that the pace of technology transitions in DRAM might be slowing. Micron has been noting for some time now that there are growing challenges associated with memory technology transitions. Compared to logic circuits (e.g., chips made by companies like Intel, and foundries like TSMC), memory chips present particular challenges. Not only does the memory chip manufacturer need to successfully image the smaller geometries, it needs to ensure that as the memory cell shrinks it still holds enough electrical charge to properly retain the information that it’s supposed to be remembering.

Exhibit 50. DRAM Price Per Megabit

$0.0001

$0.0010

$0.0100

$0.1000

$1.0000

$10.0000

Dec

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AM

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ce/M

b

DRAM price/Mb 35%/year price decline 29%/year price decline



69

Exhibit 49 and Exhibit 50 allow us to calculate an underlying growth rate for overall DRAM segment revenue. From 1990 to 2001, DRAM bit growth rate was about 77% per year and the trend for price per bit declines was 35% per year. A 77% per year bit growth rate, matched by a 35% per year price per bit drop, results in 15% revenue growth per year:

1.77*(1-0.35) =1.15

From 2001 to today, the bit growth rate appears to have slowed to 53% per year, with the price per bit decline moderating to 29% per year. This gives a revenue growth trend of 9% per year:

1.53*(1-0.29) = 1.09

If indeed the pace of memory transitions is slowing, we think that the trend toward lower DRAM price per bit might also be moderating. We think it is possible that the trend line of DRAM price per bit might show less than the 29% per year decline we have seen over the past ten years, but also that the trend line of DRAM bit growth might be less than the 53% per year of the past ten years.

Exhibit 51 and Exhibit 52 show DRAM price data. DRAM can be bought on contract in which prices are negotiated in advance or on the spot market, which offers a constantly changing price. Up to quite recently, DRAM contract prices were renegotiated twice per month. However, since about mid-2010, our understanding is that Micron has moved to setting contract prices once a month with most customers and that more recently (2014), DRAM contract negotiations may have move to a quarterly basis for some customers.

DRAM is sold on the spot market and also by contract directly from the DRAM manufacturers to systems makers. We believe that the bulk of DRAM is sold on contract. We estimate that Micron typically sells 70-90% of its DRAM in any quarter on contract. The spot market is often thought, correctly, we think, to be a leading indicator of contract pricing. The reason is that spot prices, which change daily, quickly reflect the current supply and demand situation.

When demand is rising and supply tightens, spot prices tend to rise quickly, while DRAM makers are locked into lower prices for their contracts with large PC makers. Since the contract prices represent a commitment to pay a certain price, the PC makers are reluctant to let contract prices rise at each negotiation until evidence accumulates that there is indeed more than a temporary shortage of memory. Contract prices then tend to begin rising toward spot prices, with a time lag.

Similarly, when demand is falling and there is plenty of supply, there is little demand for memory on the spot markets and spot price falls. However, the large memory customers still need memory and memory makers resist lowering prices for as long as possible. Eventually contract prices do fall though, relatively slowly, toward the lower spot prices.

PCs represent the biggest end market for DRAM, and generally, PCs require high-density chips (chips with the maximum amount of memory). Therefore, at any given time, one of the higher density memories is the volume runner for the DRAM industry. As time passes, the DRAM industry transitions to higher and higher densities. In the pricing figures we have plotted are the prices of the volume runners: 256 Mb chips from 2002 to 2004, 512 Mb chips from 2004 to 2008, 1 Gb chips from 2008 to the start of 2011, 2Gb from the start of 2011 to early 2013, and 4Gb from early 2013 to now (late 2014).

DRAM circuit technologies also change with time. Over the past few years, double data rate (DDR) DRAM, and then DDR2 DRAM began to become mainstream. DDR is a circuit design that allows the memory to do operations twice in a clock cycle rather than just once, doubling the number of calculations that the memory can achieve in any given time. DDR2 is a type of DDR memory that operates at higher frequencies. Over 2010 and 2011, the DRAM industry transitioned to using DDR3 memory, which transfers data at twice the rate of DDR2, while also featuring reduced power consumption.

Currently (November 2014), the DRAM contract price is running at close to $4.00 for a 4 Gb DDR3 chip. As can be seen from the graphs, the price for the “volume runner” DRAM chip at any given point in time can range from below $1.00 to as much as $5.00-6.00. Given that PCs typically contain 16 or 32 of the volume runner DRAM chips (8 bits make a byte), the DRAM content of a PCs can fall to as low as $20 and rise to as high as $200. We think about $50 of DRAM content per PC is “typical.”


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Exhibit 51. DRAM Spot Pricing

$-

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$7.00

Mar-02

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ep

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256Mb SDRAM 256Mb DDR 512Mb DDR 512Mb DDR2 1Gb DDR2 1Gb DDR3 2Gb DDR3 4Gb DDR3

Source: DRAMeXchange and Wells Fargo Securities, LLC Exhibit 52. DRAM Contract Pricing

$-

$1.00

$2.00

$3.00

$4.00

$5.00

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$7.00

Ap

r-02Ju

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256Mb DDR 512Mb DDR 512Mb DDR2 1Gb DDR2 1Gb DDR3 2Gb DDR3 4Gb DDR3

Source: DRAMeXchange, Micron, and Wells Fargo Securities, LLC


71

Flash memory. In the past there have been many types of non-volatile memory. Flash memory has emerged as the most important type of non-volatile memory. Other, older types of non-volatile memory include read-only memory (ROM), programmable read-only memory (PROM), erasable read only memory (EPROM), electrically erasable read-only memory (EEPROM), etc.

There are two main types of Flash memory:

(1) NAND flash. NAND flash is often used in consumer applications for the storage of large amounts of digital data. Smartphones, digital cameras, iPods and USB computer drives are important end markets for NAND flash. Tablets typically used Flash-based solid state drives (SSD) for system data storage and the use of Flash-based solid state drives (SSD) instead of hard-disk drives in notebook computers is likely to be an important emerging application for NAND flash over the next few years. (See our discussion in the Selected Technology Topics section, which follows.)

(2) NOR flash. NOR flash has slightly better performance characteristics than NAND flash, but also a higher cost. NOR flash is used primarily in applications that require relatively small amounts of non-volatile memory.

From a circuit point of view, NOR flash differs from NAND flash because it is random access, which means that information in any cell can be looked at, at any point in time. Therefore, there must be a connection (a bit line contact) to every memory cell, increasing the size of the cell. NAND flash is serial access; a whole row of cells must be read, one after another. This reduces the size of the NAND flash cell (no need to have a bit line contact per cell) reducing the cost. However, it also reduces the speed of the NAND flash, as well as increasing the error potential; if something goes wrong with one cell, it can become impossible to get information in and out of a whole row.

NAND Flash.

Exhibit 53 shows the top NAND market players for 2013. Samsung holds approximately 32% revenue share, followed by Toshiba, with a 26% share, and SanDisk, with a 16% share. From a technology point of view, the equipment needed to make NAND flash is similar to the equipment needed for DRAM manufacturing, and so, NAND capacity is fungible with DRAM. As a result, the largest NAND makers tend to also be large DRAM producers. Samsung and Toshiba have been significant manufacturers of NAND for some time.

SanDisk does not have direct ownership of memory manufacturing facilities, but participates in a number of manufacturing joint ventures with Toshiba.

Micron was involved in manufacturing NAND flash for many years at a relatively low level. In early 2006, Micron and Intel formed a joint venture, Intel-Micron Flash Technology (IMFT), which invested substantial capital in NAND flash capacity. More recently, Micron began expanding capacity in the joint venture with Intel by equipping a facility in Singapore. Since Intel decided not to contribute capital for the manufacturing equipment in this facility, Micron has a right to the bulk of the output from the Singapore NAND fab. In 2012, Intel sold some of its joint venture stake back to Micron, further increasing Micron’s ownership of NAND facilities and reducing Intel’s.


72

Exhibit 53. NAND Market Share (2013)


Toshiba, 26%

SanDisk, 16%

Micron Technology, 12% SK Hynix, 10%

Intel, 4%

Others, 1%

NAND Revenue Share 2013Total Market $28.9 billion


NAND flash is often viewed by investors as an emerging area that promises significant growth. Many memory companies have been investing substantial capital in expanding NAND flash capacity in recent years.

Exhibit 55 shows NAND megabits shipped, and Exhibit 54 year-over-year growth rates for total IC and NAND sales. Despite the large growth potential for NAND, large year-over-year NAND pricing declines have pressured revenue growth in the NAND segment.


73

Exhibit 54. NAND And IC Revenue (Year-Over-Year Growth)

(125%)

(100%)

(75%)

(50%)

(25%)

0%

25%

50%

75%

100%

125%A

ug

-04

Au

g-0

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Au

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6

Au

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Total ICs NAND

Source: Semiconductor Industry Association and Wells Fargo Securities, LLC Exhibit 55. NAND Megabits Shipped

1,000,000

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100,000,000

1,000,000,000

10,000,000,000

100,000,000,000

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s

NAND Mbits 218%/year bit growth 57%/year bit growth



74

NAND bit growth averaged around 218% per year from 2004 to 2008 and has been around 57% per year from 2008 through 2014. The use of NAND in a variety of different applications has driven high bit growth for NAND over the past several years. Wireless handsets, portable music players, and digital still cameras have been big sources of NAND bit growth in the past. Today tablets, solid state drives, and smartphones are driving high NAND bit growth. Using analysis similar to the DRAM bit growth analysis we provide in the preceding text, we conclude from SIA data that NAND bit growth has been on average:

218% per year from 2004 through 2008, and

73% per year from 2008 through the 2010-11 recovery.

The cost dynamics of NAND are, we think, very similar to that of DRAM, and so it might be expected that the trend of NAND cost per bit and price per bit declines might match the 29% per year trend for DRAM. However, as we discuss in the NAND section, there is an additional technology factor associated with NAND, which is the ability of a single NAND cell to hold more than one piece of information at a time. NAND flash can either be single-level cell (SLC), or multi-level cell (MLC). Semiconductor memory is designed to store a 1 or a 0 in a tiny piece of circuitry called a memory cell. For DRAM, each cell can store just a single 1 or 0. NAND flash can be designed as a single-level cell (just one 1 or 0) or a multilevel cell (two 1s or 0s; i.e., 00, 010, 01 or 11) per memory cell. The cell sizes of an SLC chip are the same as for an MLC chip. Therefore, an MLC chip can store twice as much information as a similar-sized SLC chip, for the same manufacturing cost, or, looking at it in another way, the cost of making a fixed amount of memory (e.g., 8 Gb) in an MLC chip is about half of what it would cost to make the same amount of memory in an SLC chip. However, since the additional storage in an MLC cell is achieved by using finer voltage divisions to decide what the stored information is, MLC chips have a lower reliability (sometimes they remember things incorrectly) than SLC chips and so SLC NAND is still used in some applications where high reliability is more important than cost.

Exhibit 56 shows how NAND price per bit has dropped over time. We have plotted price per bit, calculated from total NAND sales divided by total bit shipments. This aggregates NAND prices over many different densities of chips (i.e., today the average price per bit is calculated from sales of several different sizes of memory: 32 Gb, 16 Gb, 8 Gb, 4 Gb, 2 Gb, etc.).

The transition from SLC to MLC technology contributed to price per bit declines of about 60% per year from 2004 through 2008. The possibility of future MLC technologies, i.e., the transition to triple-level cells (TLC) from two-level cells could help offset struggles with moving to more advanced technologies, driving the trend of NAND cost per bit and price per bit declines. In the past 3-4 years, the SIA data suggest that the price per bit declines have been on the order of 20-25% per year.


75

Exhibit 56. NAND Price per Gigabit

$0.0100

$0.1000

$1.0000

$10.0000

$100.0000D

ec-0

2

Dec

-03

Dec

-04

Dec

-05

Dec

-06

Dec

-07

Dec

-08

Dec

-09

Dec

-10

Dec

-11

Dec

-12

Dec

-13

Dec

-14

NA

ND

Pri

ce/

Gb

price/Gb 60%/year ASP decline 23%/year ASP decline


Exhibit 57 shows pricing for NAND. At the time of writing of this report (H2 2014), the price of a 64Gb chip was running at close to $3 (i.e., $3x8=$24 for 64GB, or $0.38 per Gigabyte).

Exhibit 57. NAND Pricing

$-

$2.00

$4.00

$6.00

$8.00

$10.00

$12.00

$14.00

$16.00

$18.00

$20.00

Dec

-04

Mar

-05

Jun

-05

Se

p-0

5D

ec-0

5M

ar-0

6Ju

n-0

6S

ep

-06

Dec

-06

Mar

-07

Jun

-07

Se

p-0

7D

ec-0

7M

ar-0

8Ju

n-0

8S

ep

-08

Dec

-08

Mar

-09

Jun

-09

Se

p-0

9D

ec-0

9M

ar-1

0Ju

n-1

0S

ep

-10

Dec

-10

Mar

-11

Jun

-11

Se

p-1

1D

ec-1

1M

ar-1

2Ju

n-1

2S

ep

-12

Dec

-12

Mar

-13

Jun

-13

Se

p-1

3D

ec-1

3M

ar-1

4Ju

n-1

4S

ep

-14

Dec

-14

Mar

-15

Jun

-15

Pri

ce

2Gb SLC NAND Spot 2Gb SLC NAND Contract 8Gb MLC NAND Spot 8Gb MLC NAND Contract

16Gb MLC NAND Spot 16Gb MLC NAND Contract 32Gb MLC NAND Spot 32Gb MLC NAND Contract

64Gb MLC NAND Spot 64Gb MLC NAND Contract

Source: DRAMeXchange and Wells Fargo Securities, LLC


76

Solid State Drives (SSD) Versus Hard Disk Drives (HDD)

The use of NAND flash to make solid state drives for computers, especially notebook computers, is an important future trend that we think is gaining momentum. The drives are termed “solid state” drives because an old term to describe semiconductor transistors is “solid state,” as opposed to vacuum tubes. SSDs, in principle, offer the following advantages over hard disk drives (HDD), which make them particularly interesting for notebook computers:

SSDs use less power, in part because there are no mechanical parts that use power. An HDD has one or more disks that rotate at high speeds.

SSDs are more robust and tolerant to movement. In an HDD there is a disk that rotates at high speeds with a magnetic head that has to position itself a tiny distance from the disk to read the magnetic signals.

SSDs can access data more quickly. Among other things, this can improve the start-up time of a notebook. This has become a more important factor in the past year as tablets, such as the iPad, have begun to feature instant-on capabilities. As a result of these products, consumers have come to demand similar features in their notebooks. Intel has made efforts to address this demand with its Ultrabook and 2-in-1 form factor concepts of thin sub $1,000 computers with SSDs, instant on capabilities and all-day battery life.

These advantages are particularly important for notebooks. However, for solid state drives to achieve widespread use in notebooks and in computers in general, they must have a cost that is close to that of a hard disk drive. The following are some simple calculations and considerations related to the cost of HDDs and SSDs

An HDD must have a magnetic platter (the hard disc) and a sophisticated read and write head etc., so there is a minimum cost, no matter how little memory is on it. Standardized hard disk drives are not generally sold with just 1 GB of memory on them, but if they were their cost or price would probably be comparable with that of HDDs offering several tens of GB. It is only when a hard disk drive reaches high capacities (100s of GB or more) that the cost of the hard disk drive goes up (see Exhibit 58).

Unlike a hard disk drive, flash memory has a low starting cost, maybe a few dollars for the controller. The cost of any given amount of NAND flash scales fairly linearly with the amount of flash (though there is a somewhat fixed packaging and test cost for the chips.) This is illustrated in Exhibit 58. The cost-to-capacity graph for an SSD is roughly a straight line with a fairly small initial cost. Today (November 2014) the cost of 8GB of MLC NAND flash (a 64Gb chip) is about $3.00, so the NAND memory content of a 64GB drive costs about $24 (8 bits to a byte, so it takes eight 64Gb chips to make 64GB of memory).

A typical traditional notebook might have an HDD with capacity of the order of 500 GB. If we reckon that the transition to SSDs might begin to gather momentum in mainstream notebooks when the price of a 256 GB SSD is roughly the same as that of an HDD, it might perhaps be necessary for the 256 GB of NAND memory content in the drive to have a cost that is close to $30.

These calculations show that the price of NAND flash today is about 3x what it might need to be for SSDs to begin matching the cost of HDDs in mainstream notebooks. However, NAND flash is widely used in tablets.


77

Exhibit 58. SSDs Versus HDDs

Number of Gigabytes

Tot

al C

ost o

f D

rive

Solid State Drive (SSD)

Hard disk drive (HDD)

Lower NAND Cost

0Number of Gigabytes

Tot

al C

ost o

f D

rive

Solid State Drive (SSD)

Hard disk drive (HDD)

Lower NAND Cost

0

Source: Wells Fargo Securities, LLC NOR flash. Exhibit 59 shows 2013 market share for NOR flash. Micron and Spansion are two major players in the NOR flash market, with a combined share of about 50%. Exhibit 59. NOR Market Share (2013)

Micron Technology, 27%

Spansion, 24%

Macronix International, 17%

Winbond Electronics, 14%


GigaDevice Semiconductor, 5%

Microchip Technology, 3%

Eon Silicon Solution, 2%

Integrated Silicon Solution, 1%

ON Semiconductor, 1%

Others, 2%

NOR Revenue Share 2013Total Market $2.7 billion

Note: Chart created by Wells Fargo Securities, LLC (based on Gartner data) Source: Gartner, Inc., Market Share: Semiconductor Devices, Worldwide, 2013, Bryan Lewis et alia, March 31, 2014


78

NOR Flash. NOR appears to have limited growth prospects and has shrunk to a total sales level that is about one-tenth that of NAND flash. We think that the erosion in NOR demand over the past several years is associated with NAND flash emerging as the technology of choice for addressing the bulk of the non-volatile memory needs. NOR Flash typically has a higher cost, albeit also higher reliability than NAND flash. NAND is used in the bulk of high-density, high-volume applications, NOR has been increasingly relegated to the task of storing of critical system information. One common example of this in the past was in a smartphone in which high-density NAND flash was used for the large amount of memory used for data recorded by the user (e.g., the storing of photographs taken on a phone), while lower density NOR flash was used for code storage of the information needed for the communications protocols used by the phone. We believe that in recent years, even the code storage function has been usurped by NAND flash in most phones.

However, we think that NOR flash has a long-term future in various applications that require low to medium quantities of memory, which must function with high reliability over a long time period. This is true, for example, of many industrial and automotive applications, as shown in Exhibit 60.

The maximum-density segment of NOR has moved up only one notch from 2004 through 2013, from >64 Mb to >128 Mb. Admittedly though, today NOR flash chips are available in densities of up to several gigabit.

In 2004, the highest density segment (>64Mb) accounted for 1% of units (and by implication, quite a bit more than 20% of total bits and of revenue). By 2013, the highest density segment (>128Mb) was 11% of units, according to the Semiconductor Industry Association.

While the highest density segment has fallen as a percentage of units, the lowest density segment has been slowly rising. The 2Mb and lower segment moved up to 15% by 2013 from 10% of units in 2004.

Exhibit 60. NOR Bit Distribution (Chip Unit Percent)

≤ 2Mb10%

4Mb12%

8Mb13%

16Mb19%

32Mb14%

64Mb17%

> 64Mb15%

2004

≤ 2Mb15%

4Mb12%

8Mb10%

16Mb12%

32Mb13%

64Mb16%

128Mb11%

> 128Mb11%

2013

*Note: Since these pie charts represent unit percentage, the actual revenue and total bit percentages are far higher for the higher density segments than suggested in the figures. Source for both charts: Semiconductor Industry Association, Wells Fargo Securities, LLC


79

Exhibit 61 shows NOR bit shipments; Exhibit 62 shows blended price/Gb; and Exhibit 63 shows chip ASP. We believe that typically higher density products have higher chip ASP but lower price/Gb.

Worldwide NOR bit demand has been declining at a rate of about 4% per year since mid-2006.

NOR price/bit has also been falling, at a rate of about 16% per year.

The relatively slow rate of increase in NOR chip density, coupled with the steady decline in price/bit, has driven the blended NOR flash ASP down to about $0.50 today from about $3.50 in early 2004.

Exhibit 61. Worldwide NOR bit shipments

1,000,000

10,000,000

100,000,000

Dec

-02

Dec

-03

Dec

-04

Dec

-05

Dec

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Dec

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Dec

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Dec

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-12

Dec

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Dec

-14

To

tal N

OR

Mb

its

00

0s

NAND Mbits 88%/year bit growth 4%/year bit decline

* We have used an approximation that the chips in the >128Mb category of the SIA data have densities of 512Mb. We have probably underestimated slightly the total Mbits shipped in recent years. Source: SIA, Wells Fargo Securities, LLC Exhibit 62. Historical NOR Price/Gb

$1.0000

$10.0000

$100.0000

Dec

-02

Dec

-03

Dec

-04

Dec

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Dec

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Dec

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Dec

-14

NO

R P

ric

e/G

b

price/Gb 37%/year ASP decline 16%/year ASP decline

*We have used an approximation that the chips in the >128Mb category of the SIA data have densities of 512Mb. We have probably overestimated slightly the price/Mb in recent years. Source: SIA, Wells Fargo Securities, LLC


80

Exhibit 63. Historical NOR ASP

$0.00

$0.50

$1.00

$1.50

$2.00

$2.50

$3.00

$3.50

$4.00

Dec

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Ju

n-0

4S

ep

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ep

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n-1

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Ju

n-1

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ep

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n-1

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ep

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Mar

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n-1

4

Historical NOR ASP

Source: SIA, Wells Fargo Securities, LLC


81

Analog

Analog chips are generally broken out into two main segments:

(1) Standard analog chips, which are generic products mostly sold through distribution, and

(2) Application-specific analog products, which often combine both analog and digital capability (mixed-signal analog chips).

The standard analog segment has some very good business characteristics:

Low capital requirements for manufacturing. The use of cutting-edge technology generally does not improve the performance of standard analog chips in the way that it improves the performance of logic chips. Making things smaller (which is what advanced technology facilitates) helps logic chips because it helps them to work faster and do more things at the same time (packing more transistors in the same space). The performance of most standard analog chips, though, is not so much related to speed or doing many things, but in accurately measuring or reproducing the desired electrical shape. Since analog chips do not need to use the latest technology, in general, the cost of the manufacturing equipment to make analog chips is much lower than the cost of manufacturing equipment to make advanced logic chips. Many of the larger analog companies do make their own chips, but they still have relatively low capital expenses, versus logic or memory companies, which make their own chips. For example, in each of the past 14 fiscal years (FY2001-FY2014), Linear Technology, an analog company, reported capital expenditure that ranged from 1% to 13% of revenue, with this percentage being 6% or lower in 12 of the 14 years. In contrast, Micron, a memory company, in the past 13 fiscal years (FY2001-FY2013) invested between 7% and 63% of its revenue in capital expenditure, with this percentage being above 20% in 10 of the 13 years.

Long product lifetimes. In part because the performance of analog products is not dependent on rapidly changing technology, most standard analog chips have long lifetimes, stretching from years to more than a decade. In principle, this should result in a good return on circuit design costs, i.e., research and development (R&D).

Broad base of applications and customers. Many standard analog products have generic functions; they are not specific to a given standard or application. For this reason, most analog companies have a broad base of served end markets and customers.

These various considerations result in the potential for the following:

High, stable profit margin;

Low capital requirements;

Relatively little advantage from scaling in size; it appears that both large and small analog companies can coexist and flourish; and

Relatively little concentration of market or customer risk. Standard analog companies rarely have many, if any, greater than 10% customers, and usually sell their products into multiple end markets.

There is, however, one notable risk for analog companies. Because of their breadth of applications and customers, often a high percent of their revenue is sold through distribution. Some analog companies recognize revenue on sell-in to distribution, rather than sell-through. This can periodically result in excess inventory building up in distribution, which can affect revenue when the distributors take action to reduce inventory.

There is some ambiguity as to what is characterized as “standard analog” versus “application-specific analog,” leading to discrepancies in market size and market-share numbers quoted by various industry groups and market research companies. In 2013, the top standard analog market-share leader by revenue was Texas Instruments, with, according to Gartner, a 24% share, followed by Analog Devices, with a 10% share. Maxim had an 8% share, while Linear came in fourth place, with a 6% market share (see Exhibit 64).


82

Exhibit 64. Standard Analog (Excluding ASIC Analog) Market Share (2013)

Texas Instruments24%

Analog Devices10%

Maxim Integrated Products

8%

Linear Technology6%

ON Semiconductor4%

STMicroelectronics3%

Cirrus Logic3%

Intersil3%

Sanken2%

Richtek Technology

2%

Others35%


Application-specific analog businesses often have quite different characteristics from the standard analog businesses. Some application-specific analog chips are often mixed-signal chips (combining analog and digital logic functions), and for such chips there can be a need to use advanced manufacturing technology. Some application-specific analog companies do not do their own manufacturing, but instead use chip foundries. Also, there is often a higher customer and end-market concentration for any given application-specific product line, which can lead to pricing pressures. Lifetimes of applications-specific products are often considerably shorter than those of standard analog products. Investors often think of applications-specific analog companies not so much as “analog,” but more in terms of the end markets they serve, such as “communications chip companies” or “consumer chip companies.” Exhibit 65 shows the end-market distribution for the application-specific analog segment; there are five main markets, the largest of which is Communication Applications, with about 49% market share based on revenue.


83

Exhibit 65. Application-Specific Analog End Markets (2013)

Consumer8%

Computer & Peripherals

9%

Communication49%

Automotive24%

Industrial & Other10%

Application Specific Analog End Markets 2013 (Revenue)Total Market $24.1 billion

Source: Semiconductor Industry Association and Wells Fargo Securities, LLC estimates


84

Over the past ten years analog sales growth has generally trended in line with overall IC sales growth (see Exhibit 66).

Exhibit 66. IC And Analog Sales (Year-Over-Year Growth)

(60%)

(40%)

(20%)

0%

20%

40%

60%

80%

100%

Dec

-92

Jun

-93

Dec

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Jun

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-00

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-00

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-01

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Yr/

Yr

Gro

wth

Yr/Yr Change Analog Sales Yr/Yr Change IC sales



85

Programmable Logic Devices (PLD)

What PLDs Are

Programmable Logic Devices (PLD) are generic logic chips that can be programmed to perform a certain function. There are two main types of PLDs: field-programmable gate arrays (FPGA) and complex programmable logic devices (CPLDs). CPLDs are generally smaller and less expensive than FPGAs and have relatively low growth as a market, while FPGAs currently account for the bulk of the PLD market and for its growth. In 2013, the PLD market was about $4.5 billion, out of a total semiconductor market of $305 billion. Although PLDs are not a particularly large part of semiconductors as a whole (on the order of 1.5-2% of the entire semiconductor market), we discuss them briefly here because there are two stocks, Xilinx and Altera, that are important to many U.S. semiconductor investors.

A PLD consists of (a large number of) generic logic elements or logic gates, some specialized sub-circuits, and memory to store the program on-chip.

The PLD uses the information in the memory on board the chip to make connections between its logic elements so that collectively they perform a specific electronic function.

Today’s PLDs also have some specialized additional circuits, such as transceiver circuits, which the connected logic elements can use to complete the functionality of the programmed PLD.

Many types of PLDs use volatile memory (static RAM, or SRAM) to store the program information on the chip. Volatile memory loses its information when the power is switched off; therefore, these types of PLD are often used together with a separate flash memory chip, which stores the program of the PLD when the power is off (see Exhibit 67).

Exhibit 67. PLD Diagram

Memory

Logic

Element

Logic

Element

Logic

Element

Logic

Element

Logic

Element

Logic

Element

Logic

Element

Logi c

Element

Logic

Element

Logic

Element

Logic

Element

Logic

Element

Logic

Element

Logic

Element

Logic

El ement

Logic

Element

Logi c

Element

Logic

Element

Logic

Element

Logic

El ement

Logic

Element

Logic

Element

Logic

Element

Logic

El ement

Logic

Element

Memory

Logic

Element

Logic

Element

Logic

Element

Logic

Element

Logic

Element

Logic

Element

Logic

Element

Logi c

Element

Logic

Element

Logic

Element

Logic

Element

Logic

Element

Logic

Element

Logic

Element

Logic

El ement

Logic

Element

Logi c

Element

Logic

Element

Logic

Element

Logic

El ement

Logic

Element

Logic

Element

Logic

Element

Logic

El ement

Logic

Element

Source: Wells Fargo Securities, LLC


86

Designers of electronic systems have to decide between whether to use a PLD instead of a custom-designed chip, i.e., an application-specific integrated circuit (ASIC) or a standard chip designed for a specific function, i.e., an application-specific standard product (ASSP).

An ASIC is a fully custom-designed chip. Therefore, there are up-front costs associated with paying for the design of the ASIC and the initial manufacturing of the ASIC (the costs of buying the masks that contain the circuit patterns). We believe that the up-front costs of designing an ASIC could run anywhere from millions to tens of millions of dollars, while the time to design the chip could well be on the order of many months. On the other hand, an ASIC does not require additional memory to store programming the way a PLD does. Also, when a PLD is programmed for a specific function there is almost always a fair number of logic elements and other pieces of circuitry that are not used for the particular application. Therefore, a custom-designed ASIC would be expected to have a significantly smaller chip (die) size than a PLD used for the same application. The cost of making each ASIC chip is accordingly lower than the cost of making each PLD chip to do the same thing. Exhibit 68 shows this theoretical relationship. For small volume, PLDs are more cost effective since there is no up-front cost associated with a PLD. However, since the incremental cost of each chip is lower for an ASIC, for high-volume applications it can work out to be cheaper to incur the expense of designing the ASIC rather than using a PLD. There are two other considerations that play into the decision of whether to use a PLD instead of an ASIC:

o The time taken to design an ASIC and the cost and time delays associated with having to fix a design if the ASIC does not work correctly are disadvantages to using a PLD. Some systems makers use a PLD for the initial launch of a system and then as a cost-saving measure switch over to using an ASIC once the ASIC is ready.

o Since an ASIC is specifically designed for a particular application or system, it is likely to have better performance than a PLD used for the same application.

Some applications are based on widespread standards (e.g., communications standards such as Ethernet chips). Instead of needing to make a custom-designed chip, a designer of an electronic system has a choice of a chip that has already been designed for that application, an ASSP. Since the ASSPs are off-the-shelf products, they do not have the same disadvantage of ASICs in having up-front costs to the systems designs, or design risks and delays. For this reason, systems makers do not often use PLDs in applications for which there are ASSPs.

There is another choice, a “structured ASIC”, which is essentially a semi-custom chip. It can be more ASIC-like with a chip designed choosing from a library of standard circuits to put together to make a unique chip design, or more PLD-like. In the past Altera offered its Hardcopy option as a cost-reduction path for customers that have already designed solutions using Altera’s PLDs. For this, Altera used a generic chip with an array of logic elements and specialized circuitry, but no program-memory, and designs for the customer some custom metal connections between the logic elements and other circuits. The up-front cost and delay and the cost per chip of a structured ASIC are in between the corresponding costs for a PLD and for an ASIC. Altera no longer offers HardCopy-structured ASIC products for new design starts, but does continue to support HardCopy for existing designs.


87

Exhibit 68. PLDs Have A Cost Advantage For Low-Volume Applications

ASIC

Number of Chips

Tot

al C

ost

PLD

0

ASIC

Number of Chips

Tot

al C

ost

PLD

0


Exhibit 32, presented in a preceding section of this report, contains data on PLD growth relative to other semiconductor segments:

Between 1990 and 2000, PLD revenue grew at a compound annual rate of 29%, well in excess of 16% compound annual growth for semiconductor integrated circuits overall.

However, toward the end of the decade of the 1990s, one big growth driver for PLDs was the communications end market, which underwent a particularly big correction in the downturn of 2001. PLD sales declined with a CAGR of negative 21% from 2000 to 2003, while the overall IC segment declined with a CAGR of negative 8%.

From 2003 to 2007, as the electronics end markets recovered and the semiconductor industry grew, PLDs grew with a CAGR of 7%, below the overall IC CAGR of 12%.

The PLD segment significantly underperformed the broader chip group in the downturn of 2000-03 because there was a large overbuild in one of the big PLD end markets (communications infrastructure). However, there was no similar PLD-specific issue in the 2007-09 downturn and PLD declines in this period (a CAGR of negative 4%) were slightly better than overall IC declines (a CAGR of negative 7%).

PLD chips achieved a 9% CAGR, outstripping overall IC growth of 7% from 2009 to 2013. Altera and Xilinx have both suggested that the PLD segment could be at a point at which secular PLD growth could begin to run above aggregate IC growth, with PLDs eating into the broader custom chip application specific integrated circuit (ASIC) market. The growth from 2009 to 2013 could be evidence of this. However, it appears unlikely that in 2014, PLD growth will be any better than overall IC growth and might even trail total IC growth. Our current (November 2014) estimates for Altera and Xilinx imply an increase in PLD revenue of about 9% year over year for 2014, compared to our current projection that the IC market could increase 8-10% in 2014.

Altera and Xilinx have both been vocal in recent years about the potential of the PLD segment to outgrow the overall semiconductor market. There are several arguments that could be made as to why this might happen. These include the following:

Penetrating the market for ASICs by developing products on leading-edge technology.

Capturing more value by including specialized circuitry such as transceivers into the PLDs. For example, Xilinx is attempting to penetrate the embedded processing space with its Zynq product line (a family of PLDs with ARM processor cores).

Clearly from 2000 to 2007, these various factors were not enough to offset other forces that may have had a suppressive effect on PLD growth. In particular, we think that over-investment in global communication infrastructure toward the end of the 1990s took several years to work through, which hurt PLD growth because of the high exposure of PLDs to the communications infrastructure segment. PLDs did outperform the broader chip industry in 2010 and 2011, however, it appears that revenue for PLDs declined about 9% in 2012


88

compared to overall IC sales falling about 4% and only increased 2% in 2013, while total IC sales increased by around 6%, leading to a 2009-2013 CAGR that was slightly better than overall IC growth. It seems unlikely that this outperformance will continue in 2014. While it is very possible that the data of recent years indicate that PLD growth is accelerating above semiconductor growth, in our view, the evidence is not very strong. We are choosing to assume for the moment that the growth potential of PLDs is comparable to the growth potential of semiconductors overall, which we project to be 10-12% per year.

Exhibit 69 shows the top PLD market-share leaders in 2013 were Xilinx and Altera, with 51% and 37% revenue share, respectively. Other PLD companies include Lattice, 7%, and Microsemi, 4%.

Exhibit 69. PLD Market Share (2013)

Xilinx50.9%

Altera37.1%

Lattice Semiconductor7.4%

Microsemi4.4%

Others0.2%

FPGA/PLD Market 2013 (Revenue)Total Market $4.5 billion

Note: Chart created by Wells Fargo Securities, LLC (based on Gartner data) Source: Gartner, Inc., Market Share: Semiconductor Applications, Worldwide, 2013, Gerald Van Hoy et alia, March 31, 2014

Exhibit 70 shows PLD sales by end market for Xilinx and Altera for full-year 2013. Communications infrastructure (telecom infrastructure, wireless base stations, and networking equipment) represents the largest end market for PLDs, accounting for about 45% of Xilinx’s revenue and about 41% of Altera’s.

We discuss the PLD market, and Altera and Xilinx, in detail in our PLD Primer issued on October 24, 2014.


89

Exhibit 70. PLD End Markets (2013)

Telecom & Wireless

41%

Industrial Automation, Military & Auto22%

Networking, Computer & Storage19%

Other18%

Altera End Markets FY13

Communications & Data Center

45%

Industrial, Aerospace &

Defense36%

Broadcast, Consumer & Automotive16%

Other3%

Xilinx End Markets FY14 (March FYE)

Source: Xilinx , Altera, and Wells Fargo Securities, LLC estimates


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Exhibit 71 shows Altera and Xilinx’s historical quarterly revenue. Exhibit 71. Altera And Xilinx Quarterly Revenue ($ Millions)

$-

$100

$200

$300

$400

$500

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$700

Mar

-90

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-90

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-91

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-14

XLNX Revenues ALTR Revenues

Source: Xilinx, Altera, and Wells Fargo Securities, LLC


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Selected Technology Topics

Semiconductor Wafers And Chips

A semiconductor wafer is a silvery-grey disk about half a millimeter thick and typically 8 inches (200mm), or 12 inches (300mm) in diameter (see Exhibit 72). Integrated circuits are made by building up patterned layers on the surface of the wafer. Each circuit is rectangular and a few millimeters to at most a centimeter long or wide. Therefore, many copies of the same circuit (hundreds to thousands) can be made on a wafer. Typically a circuit is made up of 15-30 separate patterns (called mask layers), and the processing of the wafer requires several hundred separate steps. The fabrication of a wafer typically takes about 12-13 weeks, largely because the wafer is sitting around in the fab much of the time waiting for a machine to become free (maximum use of machines is achieved when there are always lots of wafers waiting to be processed, so that the machine can run all the time without having to wait for a wafer to need processing). When the wafer is fully processed, it is sawed up (using a circular saw) to separate each circuit. The individual rectangles are then called die, or chips.

Some companies keep some of their inventory in a “die bank.” It takes about 12-13 weeks to manufacture a wafer and about two weeks (plus additional cost) to do the testing and packaging of the chips. Keeping inventory in a die bank refers to halting the manufacturing after the wafer is fully processed and keeping the wafers in inventory (keeping the chips in die form), rather than slicing up the wafers and packaging the individual chips to make fully packaged parts. This saves the cost of testing and packaging until the chips are actually needed. It also increases flexibility of the inventory because some different product options use the same chip with differences in the way the chip is connected to the package or the choice of package type.

Exhibit 72. Photograph Of A Semiconductor Wafer (Dual Core Broadwell Microprocessors)

Source: Intel (copyright Intel, reproduced with permission)


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Manufacturing Transitions – Wafer Size and Line Width (Moore’s Law)

Wafer size is usually quoted as the diameter of the wafer (i.e., a 300 mm wafer has a diameter that is 300 mm). Prior to 2004, MOS wafers were 200 mm wafers or smaller (see Exhibit 73). It was not until 2004 that 300 mm wafers hit the market in any real volume. The 200 mm wafers have accounted for more than half of total semiconductor capacity from 2003 through 2007, with the crossover of 300 mm accounting for more capacity than 200 mm occurring in 2008.

The data of Exhibit 73 are presented in millions of square inches, rather than in absolute numbers of wafers. A 300 mm wafer makes up 2.25x the area of a 200mm wafer (the square of the ratio of the diameters), so more than 2x the number of chips can be made on a 300mm wafer. When comparing capacity of different wafer sizes, the numbers are often expressed in equivalents of a specific size. One 300mm wafer counts as 2.25 200 mm wafer equivalents. We believe capacity and output are generally measured in wafer starts per week (the number of wafers that processing is started on in any given week) or wafer outs per week (the number of wafers that processing is completed on in any given week.) Sometimes memory companies describe their capacity in terms of wafer starts per month.

The microprocessor makers (Intel and AMD) have fully transitioned to 300 mm and Intel, TSMC, and Samsung have made agreements with ASML Holding to develop 450 mm technology. Memory makers benefit from the lower cost of manufacturing chips on larger wafers and so, many of the major memory manufacturers are in various stages of transition to 300 mm production. Analog companies tend to use older technology and many analog companies are still making chips on 200 mm or even smaller wafers.

Exhibit 73. Worldwide Semiconductor Capacity by Wafer Size (Millions of square inches/Quarter)

0.0

500.0

1000.0

1500.0

2000.0

2500.0

3000.0

4Q

97

2Q

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14W

orld

wid

e S

emic

ond

uct

or

Cap

acit

y b

y W

afer

Siz

e (M

illio

ns

of s

qu

are

inch

es)

<200 mm 200 mm 300 mm

Note: Chart created by Wells Fargo Securities, LLC (based on Gartner data) Source: Gartner, Inc.: Forecast: Semiconductor Wafer Fab Capacity, Worldwide, 2Q14 Update, David Christensen et alia

Line width is the minimum size of a circuit shape that can be made (i.e., how thin a line can be made). Being able to make smaller shapes allows a designer to make chips smaller or to pack more circuitry into the same area. In the past, line width was measured in microns (um = millions of a meter. Line width is currently measured in nanometers; nm = billionths of a meter).

“Moore’s Law” is a term often used to describe the ongoing ability of the semiconductor industry to make things smaller (transition to smaller line widths), resulting in chips with lower cost and/or more capability. It is named after one of the co-founders of Intel, Gordon Moore, and Intel identifies its origin as a 1965 paper by Gordon Moore published in Electronics Magazine. Gordon Moore’s original contention was that the optimum number of devices on an integrated circuit for lowest cost per device would double every year.

Intel currently (2014) manufactures its newest Broadwell products on 14nm technology and expects to begin its transition to 10nm technology in 2016. Other leading-edge semiconductor companies design logic circuitry in 20nm, 28nm, 32nm, 45nm, 65nm, and 90nm technology, with the expectation that leading-edge manufacturing is to transition to 16nm or 14nm technology in 2015.


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The technology requirements for memory circuits are a little different from logic circuits and hence, memory chip companies sometimes have processes that are nominally more advanced that logic manufacturers and sometimes less advanced. Samsung’s terms its most advanced NAND memory process today (H2 2014) “10nm class” and its most advanced DRAM memory process “20nm class.”

In recent years a number of chip companies, especially memory companies, have commented on the increasing difficulty of moving toward more advanced technologies. Exhibit 74 shows a comparison of line-width transitions for Intel and TSMC. While there may be increasing risk that Moore’s law might slow at some point in the future, our table does not show any obvious slowing in Moore’s law as yet. In general, Intel has been maintaining a cadence of moving to a smaller line width every two years.

Exhibit 74. Line-width Transitions for Intel and TSMC (measurements in nanometers)

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015E 2016E 2017E Intel1 90 65 453

32 224 14 10

TSMC2 90 65 40 283

20 16/204 10

1For Intel, we have mapped line-width transitions into the year the corresponds with Intel’s announced launch dates. 2For TSMC we have mapped line-width transitions into the year that corresponds with the first reported quarter of sales for each line width. 3Introduction of metal gate transistors 4Introduction of 3D/FinFET transistors (expected for TSMC). TSMC’s 16nm process has 16nm transistors but uses the same metallization (connections between transistors) rules as TSMC’s 20nm process. Sources: Intel, TSMC, and Wells Fargo Securities, LLC Exhibit 75 shows worldwide semiconductor production by line width. At any given time there is a very broad spread of different technologies in use. Exhibit 76 shows the distribution of semiconductor production by line width at TSMC, the world’s largest chip foundry.


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Exhibit 75. Worldwide Semiconductor Wafer Capacity By Line Width

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

4Q

97

2Q

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Fab

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idth

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es)

14 nm

22 nm

32 nm

45 nm

65 nm

90 nm

0.13 Micron

0.18 Micron

0.25 Micron

0.35 Micron

≥0.5 Micron

0

500

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idth

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14 nm

22 nm

32 nm

45 nm

65 nm

90 nm

0.13 Micron

0.18 Micron

0.25 Micron

0.35 Micron

≥0.5 Micron

Note: Chart created by Wells Fargo Securities, LLC (based on Gartner data) Source: Gartner, Inc.: Forecast: Semiconductor Wafer Fab Capacity, Worldwide, 2Q14 Update, David Christensen et alia


95

Exhibit 76. TSMC Revenue By Technology Node--September 2014 Quarter

20nm9%

28nm34%

40nm17%

65nm13%

90nm6%

0.11/0.13um3%

0.15/0.18um13%

0.25/0.35um4%

0.50um+1%

TSMC Q3'14 Revenue by Technology

Source: TSMC and Wells Fargo Securities, LLC


96

Calculating The Number Of Circuits Of A Wafer (Die Per Wafer)

It costs a fixed amount to process a certain wafer. The smaller the die, the more die on the wafer (therefore, the less expensive each die is to make). The cost of wafer manufacturing includes not only the cost of a semiconductor chip, but also the cost of testing (making sure a chip works correctly) and packaging (enclosing the chip in plastic and creating connections so that it can be plugged into an electronic product). Packaging and testing can cost a few cents to more than a dollar, depending on the complexity of the chip. Therefore, for less expensive chips, which sell for tens of cents to a dollar or two, the package and testing costs can make up a significant portion of the total manufacturing costs. For more expensive chips (usually larger chips), which sell for tens of dollars to hundreds of dollars, the wafer manufacturing costs tend to be far larger than the package and test costs. In such cases, the number of chips on a wafer (the die per wafer) becomes an important factor in figuring out the cost of making the chips.

The following is an example:

A dual-core Intel Broadwell microprocessor has a die size of 82 mm2 (roughly the size of a thumbnail).

The area of a 300mm wafer (12 inch wafer) is 3.14x150x150 mm2 = 70,695 mm2.

Dividing 70,695 by 82 gives us a theoretical maximum of 862 die per wafer.

However, as shown in Exhibit 72, which is a picture of a Broadwell dual-core wafer, since the chips are rectangular and the wafer is round, not all the area around the edge is used and some of the chips on the edge are no good because they are not full rectangles. There are, in fact, only 789 full rectangles printed on the wafer.

Not all these chips will be good chips; some might not work properly. The number of good chips is the number of chips printed on the wafer, multiplied by the “yield.”

We can extend these calculations to estimate wafer value and wafer manufacturing cost.

Perhaps the yield is about 90%; this would give about 710 good chips on a wafer. Using an ASP of about $100 for a dual-core Broadwell chip gives us the value of the die on a typical Broadwell wafer might be close to $71,000.

If we assume a gross margin of 75% for these chips, Intel’s total cost for making the chips on the wafer might be close to $18,000. On top of the costs of processing the silicon wafer, there are packaging and test costs for each of the good chips. Backing out this “test and assembly” cost, we arrive at a manufacturing cost of the wafer that might be of the order of $14,000-$16,000.

Exhibit 20 of this report shows that the average selling price of a Taiwanese foundry wafer is close to $1,000 for an 8-inch equivalent wafer. Since the Intel wafers are 12-inch wafers (300mm wafers), they have double the area, so the equivalent foundry ASP of a 300mm wafer is about $2,000-2,500, still far below the $71,000 we calculate for Intel. However, the foundry wafer ASPs are blended ASPs for both newer and older technology of varying degrees of complexity (see Exhibit 75). The Intel Broadwell wafers are made on the very most advanced technology (14nm) with a high degree of complexity (e.g., we believe that Intel uses 10-11) layers of metal for Broadwell. The minimum number of layers of metal a semiconductor wafer might have is two layers.


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Transistors -- What They Are And Some Technical Terms Exhibit 77. Transistor

Line width

Transistor

(Top-down view)

Sou

rce

Dra

in

Transistor

(Front view)

Gate

Gate Oxide

S D

Sourc

e

Drain

Line widthLine width

Transistor

(Top-down view)

Sou

rce

Dra

in

Transistor

(Front view)

Gate

Gate Oxide

S D

Sourc

e

Drain


Exhibit 77 shows a schematic of a transistor, which is one of the basic building blocks of an integrated circuit. Integrated circuits are for the most part chips of silicon on which lots of transistors are fabricated, connected by metal lines also made on the silicon chip. What we have shown in the diagram is MOS transistor. This is made up of a gate, which is separated from the silicon below by very thin gate oxide, which separates a source and a drain. MOS stands for Metal-Oxide-Semiconductor, which is a reference to the gate (metal; see discussion on metal gates, which follows) sitting on top of an oxide, which sits on top of the semiconductor (silicon). (It turns out though, despite the term MOS, for the past 30 years, most semiconductor technologies have not used metal to make the transistor gate.)

A transistor is an on/off switch. If a certain voltage is put on the gate, current can flow from the source to the drain; the source and drain are electrically connected. If there is a different voltage on the gate, then current cannot flow and the source and drain are electrically disconnected. The gate of the transistor is typically the narrowest line that is used in all the patterns that make up an integrated circuit, and so the “line width” of any given semiconductor technology generally refers to the width of the lines used to make the transistor gates.

There are two types of MOS transistor: NMOS and PMOS. An NMOS transistor can be connected to a PMOS transistor to make a complementary MOS (CMOS) gate. Today, the bulk of logic circuit design is done using CMOS.

Metal Gate Mini-Primer

Intel was the first semiconductor company in the world to transition to using metal gate transistor technology, which it introduced on its 45nm node in 2007. In this section we provide a brief explanation of what metal gate transistors are and why the transition to metal gate transistors is so pressing.

What a metal gate transistor is. Exhibit 78 illustrates the difference between metal gate transistor and a traditional polysilicon gate transistor. Transistor A shows a typical 65nm transistor structure.

The silicon dioxide (the gate oxide) acts as an insulator to stop electrical current running from the gate to the transistor.

As each generation of technology has been made smaller, the gate oxide had to get thinner in order to allow the transistor body to electrically “see” the voltage on the gate. At the 65nm nanometer level, we believe that the gate oxide is about 30 angstroms thick. This is about six atoms thick!


98

At the 45nm level, the silicon dioxide would be so thin that it would be a poor blocker of electrical current and would allow a “leakage current” to flow through the gate. If, as an alternative, the gate dielectric were thinned less than is normal for the scaling of the transistor, the transistor would have insufficient drive current (the amount of current the transistor supplies when it is switched on), which would reduce the speed of the circuits.

Also, as everything shrinks, the source (S) and the drain (D) get so close that a leakage current can flow from source to drain when the transistor is supposed to be turned “off.”

Transistor B shows the metal gate transistor structure.

The silicon dioxide has been replaced by a “high-k” material. The “k” value can be thought of in terms of electrical density. A high-k material can be thicker physically, while looking like it is thin electrically to electric fields. Therefore, it can be made thicker than the silicon dioxide gate, but still let the body of the transistor “see” the gate voltage clearly.

Since the gate insulator is now thicker, this stops the leakage current from flowing through the gate. This gives process engineers a lot more flexibility in deciding exactly how to adjust the thickness of the gate insulator to get enough drive current out of the transistor to make the circuits fast.

Although Intel and other semiconductor manufacturers refer to this device as a metal gate transistor, we believe that the gate material is not, in fact, a pure metal, but a metal alloy (we believe that it is a metal silicide or metal silicate, which is a mixture of metal and silicon, and possibly, some other elements). There are two types of transistors used in a CMOS process, an “N” transistor (NMOS) and a “P” transistor (PMOS). The atomic properties (i.e., the work function) of the gate material (polysilicon or metal) affect how tightly the transistor can be turned “off” and how hard it can be turned “on.” If two different materials are chosen, one can be optimized for the N transistor, and the other can be optimized for the P transistor. The result is that each transistor can be turned off more tightly (less source or drain leakage) and turned on harder (more drive current) than if a polysilicon gate had been used.

Exhibit 78. Polysilicon Gate And Metal Gate Transistors

Source: Intel, AMD, and Wells Fargo Securities, LLC

Polysilicon Gate

Transistor

Metal Gate Transistor

Low Resistance Layer

Low Resistance Layer

Polysilicon gate

“Metal” gate

SiO2 gate oxide High-K gate oxide (Hafnium based)

(A) (B)

S S D D

Leakage currents


99

3-D Transistors (FinFETs or tri-gate transistors).

After having transitioned to metal gate transistors about two years ahead of any other semiconductor company, Intel made another big change in its transistor design, to 3-D transistors. Exhibit 79 shows the difference between a traditional (Planar) transistor and a 3-D transistor. In a planar transistor the gate sits on top of the place where the current flows (the channel). In a 3-D transistor the gate wraps around the channel. Since the gate is controlling the channel from three sides (hence the alternative name, tri gate), it can turn on the current more strongly (increasing the performance) or shut off the current more completely (reducing the power consumption associated with leakage).

A 3-D transition is sometimes called a FinFET because the gate looks like a fin. “FET” stands for “field effect transistor.”

Exhibit 79. Planar Transistors And 3-D Transistors

gate

gate Oxide

S D

sourc

e

drain

current

Silicon Substrate

Planar (Traditional) Transistor 3-D Transistor (FinFET, tri-Gate)

curre

nt

source

drain

Silicon Substrate

gate

gate

gate

gate oxide


Intel moved to using 3D transistors on its 22nm technology node, launching the first products using 3D transistors launched in April 2012. By the beginning of September 2014, Intel had launched 22nm products using 3D transistors in all its main server, desktop, notebook and tablet product lines and introduced 14nm 3D transistor products for fanless devices. To our knowledge, at the time of writing this report (November 2014) there is no other chip manufacturer in volume production of chips with 3D transistors.


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Lithography -- Multiple Patterning, EUV Exhibit 80. How a Lithography Tool Works

Laser Light Source

Lens

Mask

Wafer

Translation Stage

Laser Light Source

Lens

Mask

Wafer

Translation Stage


Exhibit 80 is a very rough schematic of how circuit patterns get transferred to a wafer using a lithography tool. These machines are commonly called steppers because they can image the patterns needed on only a small portion of a wafer at any time, and so they step across the wafer exposing the patterns again and again until the whole wafer is covered.

Today (2014), Intel has the most advanced technology among chip companies, manufacturing its chips on 14nm line widths. The most advanced production-worthy steppers available today use 193nm laser light to create the images. The wavelength (color) of light used provides a limitation on how small a pattern can be imaged (see Exhibit 81). An analogy to this is that a sharp pencil can draw a smaller shape than a thick crayon. In principle, the smallest shape that can be imaged by light of a given wavelength (the resolution of the light) is half the wavelength of the light used, and so, with 193nm steppers, it becomes very difficult to accurately create shapes of line width less than 100nm.


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Exhibit 81. The Wavelength of Light Affects the Smallest Possible Pattern That Can Be Easily Imaged

Source: Wells Fargo Securities, LLC Over the years, the semiconductor industry has implemented a number of imaginative technical “tricks” to push the resolution of the steppers below the theoretical limits associated with the wavelength of the light source. These include the following:

Immersion lithography--running the light through a liquid rather than air. This increases the “numerical aperture” of the optical system, improving the ability of the system to image features that are smaller than the wavelength of the light used.

Doubling patterning (to be followed by multiple patterning in the future). Double patterning involves using the stepper twice to create two different patterns, creating very small shapes associated with the overlap of the two separate patterns. Multiple patterning refers to using more than two separate exposures to create the final pattern.

The move to double patterning roughly doubles the number of steppers needed for each of the smallest patterns (each critical layer) needed in the wafer manufacturing process. Since the steppers are arguably the most expensive individual pieces of equipment in a fab (the most advanced steppers are priced at tens of millions of dollars each) the need for double and, in the future, multiple patterning, will likely drive up the capital cost of equipping a fab.

Given that one of the key difficulties in the creation of the circuit patterns is that the steppers use a wavelength of light that is too long to easily image the patterns, an obvious solution is move to a shorter wavelength of light. This is what the semiconductor industry is trying to do, by moving to using “Extreme Ultra Violet” (EUV) light. ASML is working with 13.5nm light sources for its EUV machines. Violet is the shortest wavelength that a human eye can normally see, about 400nm. The 193nm used in today’s steppers is called ultra violet, a shorter wavelength than violet. Hence, the even shorter wavelength of 13.5nm is called extreme ultra violet. There are many difficulties, though, in working with such a short wavelength of light. One of the bigger ones is that it is difficult to make a laser that can produce enough brightness of 13.5nm light to expose the pattern in a short time, resulting in low throughput of the stepper. As a result, it takes a long time to process each wafer. There are other difficulties associated with working with EUV light, as well. For example, 13.5nm light gets blocked by the glass typically used to make lenses so that curved mirrors are needed to focus the light (reflective optics), rather than passing the light through normal lenses (transmission optics).


102

Appendix A. Semiconductor Companies (Figures In Millions Of Dollars, Except Per Share Data) Mkt Cap (millions)

Chip Revs ($ millions)

Description Chip Category

Company Ticker 11/13/2014 2013INTEL INTC $161,392 $52,708 Chips For PCs Microprocessors SAMSUNG* Division of Samsung $30,636 Memory Chips DRAM, NAND TSMC (Taiwan Semiconductor) TSM $114,349 $20,083 Makes Wafers For Fabless

Companies Wafer Foundry

TEXAS INSTRUMENTS TXN $54,167 $12,205 Broad-Based Analog, DSP TOSHIBA* Division of Toshiba $11,277 Memory Chips NAND QUALCOMM QCOM $116,864 $25,470 Chips For Wireless Handsets Application Specific Analog,

Specialized Logic STMICROELECTRONICS STM $6,072 $8,088 Broad-Based Analog, Microcontrollers, ASSPs RENESAS* Not listed in US $7,979 Broad-Based Microcontrollers, Memory, Etc. HYNIX* Not listed in US $12,625 Memory Chips DRAM, NAND MICRON TECHNOLOGY MU $35,327 $11,281 Memory Chips DRAM, NAND BROADCOM BRCM $24,361 $8,219 Chips For Communications Application Specific Analog,

Specialized Logic ADVANCED MICRO DEV AMD $2,101 $5,299 Chips For PCs Microprocessors, Graphics Processors

SANDISK SNDK $20,483 $6,170 Memory Chips NAND MATSUSHITA (PANASONIC)* Division of Matsushita $2,018 Broad-Based Discretes, App. Specific Analog,

Microcontrollers Etc. FREESCALE FSL $5,997 $4,186 Broad-Based Application Specific Analog,

Microcontrollers Etc. NXP SEMICONDUCTOR NXPI $16,937 $4,815 Broad Based (Consumer

Applications) Application Specific Analog, Specialized Logic

UMC (UNITED MICROELEC) UMC $5,378 $4,165 Makes Wafers For Fabless Companies

Wafer Foundry

SONY* Division of Sony $3,488 Chips For Consumer Electronics Specialized Logic, Application Specific Analog

INFINEON IFX $10,655 $5,290 Broad-Based, Esp. Communications Application Specific Analog, Microcontrollers Etc.

MARVELL TECH GROUP MRVL $6,857 $3,404 Chips For Communications & Storage

Application Specific Analog, Specialized Logic

NVIDIA NVDA $10,646 $4,130 Graphics Chips For PCs Etc. Graphics Processors MEDIATEK* Not listed in US $4,586 Chips For Communications Application Specific Analog,

Specialized Logic ROHM* Not listed in US $2,591 Broad-Based ICs And Discretes ANALOG DEVICES ADI $15,791 $2,640 Broad-Based Analog, DSP FUJITSU* Division of Matsushita $1,542 Broad-Based Microcontrollers, ASICs MAXIM INTEGRATED PRD MXIM $8,332 $2,419 Broad-Based Analog ON SEMICONDUCTOR ONNN $3,613 $2,783 Broad-Based Analog, Discrete XILINX XLNX $11,467 $2,297 Broad-Based PLDs SUNPOWER SPWR $3,828 $2,508 Solar Chips Solar SILICONWARE SPIL $4,400 $2,333 Packaging and Testing AVAGO AVGO $21,997 $2,653 Communications Optical Components SHARP* Division of Sharp $1,619 Broad-Based Optoelectronics, ICs ALTERA ALTR $10,650 $1,733 Broad-Based (Programmable Logic) PLDs

NANYA TECHNOLOGY* Not listed in US $1,497 Memory Chips Dynamic RAM ATMEL ATML $3,157 $1,386 Broad Based (Microcontrollers,

Memory) Microcontrollers, EPROM

FAIRCHILD SEMI INT'L FCS $1,881 $1,405 Broad-Based (Analog, Discretes) Analog, Discrete SEMICONDUCTOR MF ADR SMI $3,607 $2,071 Makes Wafers For Fabless


VISHAY* Division of Vishay $1,357 General Purpose Discretes MITSUBISHI* Division of Mitsubishi $1,551 Sensors And General Purpose Transistors, Optical Semiconductors LINEAR TECHNOLOGY LLTC $10,282 $1,317 Broad-Based (Analog) Analog ROBERT BOSCH* Division of Bosch $1,785 Sensors, Application Specific

Devices Sensors, Automotive ASSPs

MICROCHIP TECH MCHP $8,718 $1,868 Broad-Based (Microcontrollers) Microcontrollers NICHIA* Not listed in US $1,519 Optical Semiconductors (LEDs) Optical Components POWERCHIP SEMICONDUCTOR*

Not listed in US $229 Memory Dynamic RAM, NAND-Based Flash

SPANSION CODE $1,322 $1,035 Memory Chips NOR Flash Memory TTM TECHNOLOGIES INC. TTMI $578 $1,368 Broad-Based PCB Manufacturer SEQUANS COMMUNICATION SQNS $87 $14 Wireless Application Specific Analog SKYWORKS SOLUTIONS SWKS $11,559 $1,844 Wireless Application Specific Analog NOVATEK* Not listed in US $1,397 General Purpose Logic, Application

Specific Devices ASSPs, LCD Drivers

RF MICRO DEVICES RFMD $3,852 $1,173 Wireless Handsets Applications Specific Analog OSRAM* Dividion of OSRAM $1,328 General Purpose Optical Semiconductors CREE CREE $4,166 $1,530 Light Emitting Diodes Optoelectronics WINBOND ELECTRONICS* Not listed in US $961 Broad-Based Memory, Microcomponents, Compute

& Consumer ASSPs CYPRESS SEMICONDUCTR CY $1,635 $723 Memory And Programmable Logic SRAM, PLDs OMNIVISION TECH OVTI $1,554 $1,459 Image Sensor ICs For Handsets

And Cameras Optoelectronics

INTERSIL HLDG ISIL $1,695 $575 Broad-Based Analog MACRONIX INTERNATIONAL* Not listed in US $670 Memory Flash Memory, Mask ROM


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REALTEK SEMICONDUCTOR* Not listed in US $950 Communications Applications Specific Analog PMC-SIERRA PMCS $1,523 $508 Communciations Application Specific Analog,

Specialized Logic ARM HOLDGS ADR ARMHY $19,397 $1,119 Processors For Wireless (IP) Intellectual Property/Processors PROMOS TECHNOLOGIES* Not listed in US $114 Memory DRAM INTEGRATED DEVICE IDTI $2,641 $476 Broad-Based, Esp. Communications SRAM, Appl. Spec. Analog

DIODES DIOD $1,255 $827 Broad-Based (Analog, Discretes) Application Specific (Discrete And Analog)

CHIPMOS TECHNOLOGIES BERMUDA LTD.

IMOS $649 $649 IC Test and Packaging Services IC Test and Packaging Services

MICROSEMI MSCC $2,606 $1,021 Power Management Analog, Discrete TOWER SEMICONDUCTOR TSEM $524 $505 Makes Wafers For Fabless

Companies Specialty Wafer Foundry

SUN EDISON (formerly MEMC) SUNE $4,805 $1,985 Makes Silicon Wafers and sells solar energy solutions

Polysilicon and silicon wafers

SILICON LABORATORIES SLAB $1,940 $580 Wireless Application Specific Analog BOOKHAM BKHM $179 $477 Optical Communications Optoelectronics OCLARO INC. BKHM $179 $477 Communciations Optoelectronics SEMTECH SMTC $1,736 $595 Broad-Based Analog And Mixed-Signal II-VI IIVI $820 $623 Industrial Laser Components Optoelectronics STANDARD MICROSYSTMS* (Merged with Microchip) $207 Broad-Based Application Specific Analog,

Specialized Logic RICHTEK TECHNOLOGY* Not listed in US $361 Broad-Based Applications Specific Analog IXYS SYXI $366 $313 Broad-Based Power Mosfets And Mixed Signal ICs CIRRUS LOGIC CRUS $1,235 $772 Chips for Audio and Industrial

Applications Analog And Mixed-Signal ICs

RAMBUS RMBS $1,316 $272 Memory (IP) Intellectual Property - Memory TESSERA TECHNOLOGIES INC. TSRA $1,664 $169 Chip Packaging Technology (IP) Intellectual Property - Chip Packaging

POWER INTEGRATIONS POWI $1,566 $347 Broad-Based Analog ICs LATTICE SEMICONDUCTR LSCC $784 $333 Broad-Based PLDs MICREL MCRL $709 $237 Broad-Based Analog, Mixed-Signal ICs DIALOG SEMICONDUCTOR* Not listed in US $903 Broad-Based Applications Specific Chips RAYDIUM SEMICONDUCTOR* Not listed in US $367 Chips for displays (LCD Drivers) Applications Specific Analog SIGMA DESIGNS SIGM $144 $199 Chips for consumer (IPTV And

Media Players) Specialized Logic

INTEGRAT SILICON SOL ISSI $417 $310 Memory SRAM and DRAM APPLIED MICRO CIRCTS AMCC $496 $221 Communications Application Specific Analog DSP GROUP DSPG $225 $151 Broad-Based ICs MONOLITHIC POWER SYS MPWR $1,761 $238 Chips for Power Management Analog ANADIGICS ANAD $68 $134 Wireless Communciations Applications Specific Analog CAVIUM CAVM $2,851 $304 Communciations (Network

processors) Specialized Logic

EMCORE CORP. EMKR $162 $163 Fiber Optics, Solar Power Optoelectronics SUNPLUS* Not listed in US $103 Chips for Consumer Applications Application Specific IKANOS COMMUNICATION IKAN $50 $80 Chips For Communications Applications Specific Analog SILICON IMAGE SIMG $431 $276 Communications for consumer

(HDMI) Application Specific Analog

INVENSENSE INVN $1,284 $249 Motion sensing (audio) for consumer

Application Specific Analog

VIA TECHNOLOGIES* Not listed in US $156 Computing Applications Processors and Logic VITESSE SEMICONDUCTR VTSS $237 $105 Communications Application Specific Analog FARADAY TECHNOLOGY* Not listed in US $203 Computing and Communcations Intellectual Property for Applications

Specific Chips INPHI CORPORATION IPHI $535 $103 Computing and Communcations Analog/Mixed Signal Ics MONTAGE TECHNOLOGY MONT $589 $111 Digital set top boxes and server

DRAM Analog/Mixed Signal Ics

ENTROPIC COMMUNICATIONS ENTR $233 $259 Set top box (Consumer) Analog/Mixed Signal Ics PERICOM SEMICONDUCT PSEM $251 $127 Communciations Application Specific Analog MELLANOX TECHNOLOGIES MLNX $1,965 $391 Chips For Communications Application Specific Analog EXAR EXAR $420 $128 Chips For Communications Application Specific Analog SILICON MOTION ADR SIMO $744 $225 NAND Flash, Digital Consumer,

Handsets Specialized Logic

O2MICRO INT'L ADR OIIM $52 $74 Power Management Analog ALI (Acer Labs Inc.)* Not listed in US $140 Computer Communications

(chipsets etc.) Specialized Logic

KOPIN CORP. KOPN $242 $23 Semiconductor Materials Wafer Manufacturer SILICON INTEGRATED SYSTEMS*

Not listed in US $17 Computer and consumer applications

Logic

ADVANCED ANALOGIC TECHNOLOGIES INC.*

Acquired by Skyworks $80 Power Management Analog ICs

PIXELWORKS PXLW $118 $48 Digital TVs, Digital Consumer Application Specific Analog, Specialized Logic

8X8 EGHT $712 $122 VoIP Services ICs ON TRACK INNOVATIONS OTIV $81 $20 Chips for Smart Cards Applications Specific Logic and

Wireless TRANSWITCH TXCC $0 $18 Chips For Communications Application Specific Analog CEVA CEVA $323 $49 Handsets And Consumer Electronics IP For DSPs

ENE TECHNOLOGY* Not listed in US $25 Broad-Based Analog QUICKLOGIC QUIK $178 $26 Broad-Based PLDs MONOLITHIC SYS TECH MOSY $83 $4 Memory (Intellectual Property) Embedded DRAM ALLIANCE MEMORY* ALSC $26 $10 Memory DRAM, SRAM (controllers and IP) AUDIENCE ADNC $92 $160 Audio SUN EDISON SEMICONDUCTOR SEMI $691 $921 Semiconductor Materials Wafer Manufacturer

KNOWLES CORP. KN $1,617 $1,215 Chips for Audio and Industrial Applications

Analog And Mixed-Signal ICs

INVENSENSE INVN $1,284 $249 Consumer and Industrial Analog And Mixed-Signal ICs AMBARELLA AMBA $1,467 $158 Broadcast Infrastructure and

Cameras Analog And Mixed-Signal ICs

INPHI IPHI $535 $103 Infrastructure and Computing Analog And Mixed-Signal ICs SENSATA TECHNOLOGIES ST $7,767 $1,981 Broad-Based Sensors NEOPHOTONICS NPTN $98 $282MAGNACHIP SEMICONDUCTOR MX $401 $857M/A-COM TECHNOLOGY* MTSI $1,097 $159


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MINDSPEED TECH Acquired by M/A-COM Chips For Communications Application Specific Analog MSTAR SEMICONDUCTOR* Acquired by MediaTek Application Specific Devices Consumer ASSPs ELPIDA Acquired by Micron $2,467 Memory Chips DRAM CAMBRIDGE SILICON RADIO* In processor of being acquired by

Qualcomm$1,025 Wireless Communications Applications Specific Analog

INTERNATIONAL RECTIFIER CORP.

IRF, Infineon acquisition expected to close late 2014

$2,855 $1,040 Power Management Analog, Discrete

PEREGRINE SEMICONDUCTOR acquired by Murata Application Specific Devices ASICs, ASSPs APTINA Acquired by ON Semiconductor Image Sensor ICs For Handsets

And Cameras Optoelectronics

LSI LOGIC Acquired by Seagate Chips For Comms And Storage Application Specific Analog, Specialized Logic

TRIQUINT SEMICONDCTOR Acquired by RFMD RF Wireless Analog ICs SUPERTEX Acquired by Microchip Power Management Analog PLX TECHNOLOGY Acquired by Avago Communciations Application Specific Analog NATIONAL (Now part of TI) NSM Broad-Based Analog VOLTERRA SEMICNDCTOR Acquired by Maxim Power Management Analog WOLFSON MICROELECTRONICS Acquired by C irrus Chips for Audio (Consumer) Application Specific Analog

HITTITE MICROWAVE Acquired by ADI Wireless Application Specific Analog SPREADTRUM COMMUNICATIONS

Acquired by Chinese government ASSPs Wireless ASSPs

IBM* In process of being acquired by Globalfoundries

$1,437 Microprocessors, Makes Wafers For Others

Microprocessors, Wafer Foundry

LOGIC DEVICES LOGC Imaging Logic SIMPLETECH STEC Memory (Solid State Drives) NAND Flash (Solid State Drives) STAKTEK STAK Memory Module Tech. and IP for Stacking MIPS TECHNOLOGIES Sold to Imagination Technologies Broad-Based Processors (Intellectual property) TRIDENT MICROSYS Filed for bankruptcy January 2012 Digital TV And Multimedia Mkts Analog SIGE SEMICONDUCTOR Acquired by SkyWorks Chips For Communications

(wireless) Applications Specific Analog

ZARLINK SEMICONDCTR Acquired by Micrsemi Communications And Healthcare ICs RALINK TECHNOLOGY Merged with MediaTek Communications Application Specific Analog NETLOGIC Acquired by Broadcom General Purpose Memory, Microcomponents ATHEROS COMMUNIC Acquired by Qualcomm Wireless Communciations Applications Specific Analog NATIONAL (Now part of TI) NSM Broad-Based Analog SRS LABS Acquired by DTS Audio Application Specific Analog RAMTRON INT'L Acquired by Cypress Broad-Based Specialized Memory and

Microcontrollers ACTEL Acquired by Microsemi Corporation Broad-Based PLDs MICROTUNE Acquired by Zoran Corporation Cable, DTV, Automotive Tuners Analog SILICON STORAGE TECHNOLOGY

Acquired by Microchip Technology Memory Memory Chips (Flash)

CALIFORNIA MICRO DEVICES CO COM

Acquired by ON Semiconductor Wireless Handsets and Consumer Discretes

ZILOG Acquired by IXYS Corporation Broad-Based Microprocessors & Microcontrollers CENTILLIUM COMMUNI. Acquired by TranSwitch Corporation Communications Application Specific Analog CHARTERED SEMICONDUCTOR Acquired by GlobalFoundries Makes Wafers for Fabless


CONEXANT SYSTEMS Privately Owned by Golden Gate Capital

Communications and Consumer ICs For Networking

HI / FN INC COM Acquired by Exar Corporation Network and Storage Security ICs MATHSTAR Merged with Sanjan Industrial, DSP ICs (FPOAs) NEC Division of NEC Broad-Based Very Broad QIMONDA AG SPONSORED ADR Filed for Bankruptcy in Multiple

Jurisdictions Memory Chips DRAM

SIRF TECHNOLOGY HOLDINGS Acquired by CSR PLC in 2009 Wireless Communications (GPS) Application Specific Analog TECHWELL Acquired by Intersil Communications Chips Analog and Mixed-Signal ICs TRANSMETA CORP. Acquired by Novafora, Ceased

Operations August 2009 Semiconductor Manufacturing IP Semiconductor Manufacturing

TVIA INC COM Tvia, Inc. Reorganized Out of Bankruptcy Aug. 3, 2011

Digital TVs Specialized Logic

VIRAGE LOGIC Acquired by Synopsys Memory (Controllers) Logic for Memory WHITE ELEC DESIGNS Acquired by Microsemi Defense, Commercial Embedded Components VERIGY LIMITED Acquired by Advantest Test & Equipment *For companies listed in the United States that are primarily chip companies, we have listed total revenue. For companies not listed in the United States, or divisions of larger companies, we have included only semiconductor revenue. Source: FactSet, Company reports and Wells Fargo Securities, LLC


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Appendix B: Glossary

3G/4G–The third and fourth generations of mobile communications standards used for mobile web access, IP telephony, gaming services, HD mobile TV, and cloud computing.

A/D converter--see analog-to-digital converter

analog--something that processes information in the form of continuous voltage and current. A circuit can be analog or digital. A digital circuit thinks in terms of just a “1” or a “0,” whereas an analog circuit has to deal with everything in between (0.1, 0.15, 0.2 …. etc.). Analog circuits have different requirements and sensitivities from digital circuits and so require different design and manufacturing techniques. Typically analog chip manufacturing does not require leading-edge equipment and so is less capital intensive than digital chip manufacturing. Both logic chips and memory are typically digital.

analog-to-digital converter--data conversion chip that takes a continuous analog signal and converts it to a stream of digital numbers by making measurements of the height (voltage of the signal) at regular time intervals.

Applications processor--Applications processors are processors used as the brains to run applications in tablets and smartphones.

ASIC--(Application Specific Integrated Circuit)--a custom-designed chip, as opposed to an off-the-shelf generic chip.

ASSP--(Application Specific Standard Products)--a name for something that is not an ASIC – a standard product designed for a specific purpose.

Baseband processor–a device in a network interface that manages all of the radio functions, including wi-fi and Bluetooth.

bit--see megabit

byte--a byte is 8 bits. See megabit.

capacitor--a device in electronic circuits that can store electric charge (electrons).

capacity utilization--actual output of a semiconductor fab or group of fabs as a percent of what the fab is theoretically capable of. As a rule of thumb, we consider 90-100% capacity utilization as a healthy level of utilization. In principle, 100% is the maximum capacity utilization a fab or a company can achieve. TSMC has in the past quoted capacity utilization of as much as 110%.

chip--a piece of semiconductor containing a circuit. Also called a die.

clock, clock frequency--many chips are synchronous in operation, which means that a clock signal needs to be generated and all calculations or other operations in the circuit wait for the next beat of the clock before they happen. This makes sure that signals are transferred at the same time, avoiding errors that may occur as a result of one thing happening earlier than something else. The higher the clock frequency, the more things that can happen per second and the more the chip can achieve. Typical clock frequencies are 100s of megahertz (hundreds of million times per second) or several gigahertz (several billion times per second).

computing cloud--a network of large data centers and high-end servers which facilitate remote access to centrally located software programs via a suitable internet connection. The idea of a computing cloud is to spread an extremely large amount of computing power to a variety of users who individually lack the resources to acquire such a high volume of data.

CMOS--“Complementary MOS.” A type of integrated circuit. Most digital semiconductor circuits are CMOS these days. A CMOS circuit uses two types of transistor, NMOS and PMOS. The predecessor to CMOS logic was NMOS logic. A circuit might also be bipolar rather than CMOS. And bipolar circuits are occasionally used for analog applications, but CMOS has also achieved widespread use even in analog. See definition of MOS.

contract price, contract market--semiconductor memory can be bought on contract, in which prices are negotiated in advance, twice per month, or on the spot market, which offers a constantly changing price. The bulk of DRAM is sold on contract, but the spot market is often thought to be a leading indicator of contract pricing.


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CPU (central processing unit)--the brain of a computer, also known as a microprocessor.

D/A converter--see digital-to-analog converter

DDR, DDR2--DDR stands for double data rate. DDR and DDR2 are types of DRAM memory, in which operations can happen twice in a clock cycle (hence the term double).

data converter--a digital-to-analog or analog-to-digital chip. See digital-to-analog converter and analog-to-digital converter.

die--a square of semiconductor (usually silicon) containing a circuit.

die bank--this refers to chip companies sometimes choosing to keep their semiconductor inventory in the form of fully processed wafers rather than cutting up the wafers into chips and packaging them.

die size--The size of a semiconductor chip. Semiconductor circuits are created on wafers of silicon, round discs 200mm or 300mm in diameter. An individual chip (die) can have a size ranging from a square or rectangle with a length/width anywhere from 1 mm to more than 1 cm. It is a fixed cost to process a wafer, and so the smaller the die, the more die there are on a wafer, which decreases the cost of each die.

die per wafer--the number of chips that can be made on a single wafer. See “die size” definition.

digital-to-analog converter--data conversion chip that takes a stream of numbers and makes them into a continuous signal.

diode--one of the simplest types of semiconductor device that can be made. A diode allows electricity to flow in one direction but not the other. If the diode is made of the right type of semiconductor, when current flows through it, it will give off light. This is a light emitting diode (LED).

discretes--A semiconductor product that is just a single device (e.g., a transistor) rather than an integrated circuit with many devices (up to hundreds of millions of transistors) all connected together on the same chip. Typically discretes are fairly inexpensive chips (priced in the range of cents to tens of cents.) The silicon cost of discretes is relatively low, packaging costs can be fairly significant.

DRAM (dynamic random access memory)--a type of memory that is most commonly used as the main memory in a computer. DRAM is “volatile” memory, which means that it forgets what it is supposed to remember when the power is switched off, as opposed to “non-volatile” memory (flash memory is one type of non-volatile memory), which remembers its information even with the power off. See RAM.

DSP (digital signal processors)--a chip that is designed to be particularly good at computations used in processing communications signals.

equivalent wafers--see wafer equivalent.

EUV–extreme ultra violet. Violet is the shortest wavelength that a human eye can normally see, about 400nm. The 193nm used in today’s steppers is called ultra violet – a shorter wavelength than violet. The semiconductor industry is trying to move to an even shorter wavelength of light for imaging chip circuits, 13.5nm, which is called extreme ultra violet.

fab--a factory (fabrication facility) for processing semiconductor wafers to create semiconductor chips.

fabless--refers to a company that does not have its own fab, but rather, outsources its chip production to a company with fabs (examples of fabless companies include Broadcom and Nvidia, while fab companies include AMD, Intel).

floor capacity--the capacity a fab would have if it was filled completely with semiconductor manufacturing equipment. Often only part of a large fab is initially filled with equipment, and so installed capacity is less than floor capacity.

foundry--typically a semiconductor manufacturer that makes chips for fabless companies. TSMC (Taiwan Semiconductor Manufacturing Corporation) is the world’s largest foundry, UMC (also in Taiwan) the second largest, and Chartered Semiconductor (Singapore) the third largest.

frequency--see clock frequency.

gigabit--A quantity of memory. 1000 megabits (actually 1024 megabits). See megabit.


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gigabyte--A quantity of memory. 1000 megabytes (actually 1024 megabytes). See megabit.

gigahertz (GHz)--a billion times per second. See clock.

hard disk drive (HDD)--the standard bulk memory device in a personal computer. Most computer contain DRAM for storing the information that the microprocessor needs immediately, when the computer is switched on, and bulk memory to store all the files permanently, even when the computer is switched off. In a hard disk drive the information is stored on one or more magnetic disks (hard disks).

HDD--see hard disk drive

IC--See integrated circuit.

integrated circuit (IC)--A silicon chip on which many (ranging from tens of transistors to hundreds of millions of transistors) are connected together, all on the same chip. See discretes for comparison.

installed capacity--The manufacturing capability of the manufacturing equipment in a fab. This is sometimes less that floor capacity (see the definition of floor capacity).

interface chips--Analog chips that provide the interface onto standardized communications signal lines; they are the chips responsible for driving the electrical voltages/currents down the lines. For example, in a computer, there would be some PCMCIA chips for driving signals down a PCMCIA bus.

linear--Another word for analog; see analog

linewidth--A semiconductor circuit is made by creating a series of patterns in a number of semiconductor, insulator and metal films that are laid one on top of another. The narrowest width that can be used in a pattern is referred to as the line width. As technology develops, the line width drops, and so each feature can be made smaller, resulting in either smaller chips, or more typically, chips of the same size that contain more transistors and other devices on them.

lithography tool–machines used in semiconductor manufacturing to transfer circuit patterns onto semiconductor wafers. These machines are commonly called steppers because they can image the patterns needed on only a small portion of a wafer at any time, and so they step across the wafer exposing the patterns again and again till the whole wafer is covered.

logic chip--a chip that thinks (can do computations or make decisions), as opposed to a memory chip (a chip that remembers) or an analog chip (a chip that deals with sending or receiving signals). Examples of logic chips include microprocessors, microcontrollers and programmable logic devices.

LTE (Long Term Evolution)--The wireless standard for high-speed data for mobile phones and data terminals.

maintenance capex (maintenance capital expenditure)–the level of capital spending, by a chip manufacturer, that is just enough to keep the manufacturing capacity constant. There is a certain minimum level of spending needed, in part to replace old or obsolete manufacturing equipment. If capital spending drops below maintenance capex, then total manufacturing capacity will fall.

megabit--a bit refers to a single “1” or “0”. Memory size is measured in the number of bits (the number of separate 1s or 0s) that a memory can store. A megabit is approximately a million bits. Because of the way memory locations are defined (as a string of 1s and 0s), the amount of memory provided in a chip is not exactly a million bits for a megabit, but actually some number that is 2n. In fact, a megabit is 1,048,576 bits. The fact that the amount of memory is always defined as a power of two also explains the various choices of standard memory size (e.g., 1 Gb, 2Gb, 4Gb etc.)

megabyte--A quantity of memory. 8 megabits make up a megabyte. See megabit.

megahertz (MHz)--a million times per second. See clock.

memory--a chip that remembers information. The two most common types of memory are DRAM (volatile memory) and flash (non-volatile memory). Memory chips tend to be commodity-like in their sales characteristics; prices change on a daily basis on the spot market and contract prices are generally renegotiated twice per month. The commodity-like nature of memory makes memory manufacturing very capital intensive, since leading-edge technology is needed to get the lowest costs (the smaller a chip can made, the less expensive


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it is.) Most of the major memory companies run their own fabs; there are relatively few fabless memory companies.

memory cell--a piece of circuitry that makes up one unit of memory in a memory chip.

microcontroller--a simple thinking chip--like a microprocessor but smaller and less smart. Electronic devices like washing machines have microcontrollers to do the simple thinking required to run themselves.

microprocessor--a chip that is used as the thinking part of a computer. It is sometimes call a CPU or the central processor unit.

MLC--see multi-level cell

Modem – a device that modulates an analog carrier signal to encode digital information and also demodulates carrier signals to decode transmitted information, producing a signal that can be easily transmitted and decoded to reproduce the original digital data.

Moore’s Law. Moore’s Law” is a term often used to describe the ongoing ability of the semiconductor industry to make things smaller (transition to smaller linewidths), resulting in chips with lower cost and/or more capability. It is named after one of the co-founders of Intel Gordon Moore, and Intel identifies its origin as a 1965 paper by Gordon Moore published in Electronics Magazine. Gordon Moore’s original contention was that the optimum number of devices on an integrated circuit for lowest cost per device would double every year.

MOS (metal oxide semiconductor)--This is a reference to a type of transistor (see definition of transistor below), the one that is most commonly used in integrated circuits today. The term MOS is misleading since almost all MOS transistors today are really silicon-oxide-silicon structures. Intel is transitioning to “metal-gate” transistors, but we believe that even with these new transistors the metal gate is not a pure metal. There are two types of MOS transistors: NMOS and PMOS. Together NMOS and PMOS transistors can be connected to create a CMOS (complementary MOS) circuit. See definition of CMOS above.

multilevel cell (MLC)--a NAND memory cell that can store more than one bit--a “1” and/or “0” at the same time. Today NAND MLC is invariably a two-level cell--two “1”s and/or zeros stored in one cell: 00, 10, 01, or 11.

nanometer--a billionth of a meter, denoted by the symbol nm. Semiconductor manufacturing technology is described by the smallest width of a line that can be created in that technology. Currently, the most advanced technology is 45nm.

NAND flash--as opposed to NOR flash--NAND is a type of flash memory (non-volatile) that is used in non-volatile memory applications in which low cost and/or a large amount of memory is needed, typically consumer applications such as storage for digital cameras, music storage for iPods, and removable storage for computers. From a circuit point of view, NOR flash differs from NAND flash because it is random access, information in any cell can be looked at, at any point in time. Therefore, there must be a connection (a bit line contact) to every memory cell, increasing the size of the cell. NAND flash is serial access, a whole row of cells must be read, one after another. This reduces the size of the NAND flash cell (no need to have a bit line contact per cell) reducing the cost. However, it also reduces the speed of the NAND flash, as well as increasing the error potential; if something goes wrong with one cell it can become impossible to get information in and out of a whole row.

Non-volatile memory--memory that retains its data when the power source is removed.

NMOS--a type of MOS transistor (see definition of MOS above) in which the electrical current comes from the flow of electrons (negative charged particles, hence the “N” in NMOS).

NOR flash--as opposed to NAND flash. NOR flash is used mainly for code storage in cell phones. From a circuit point of view, NOR flash differs from NAND flash because it is random access; information in any cell can be looked at, at any point in time. Therefore, there must be a connection (a bit line contact) to every memory cell, increasing the size of the cell. NAND flash is serial access; a whole row of cells must be read, one after another. This reduces the size of the NAND flash cell (no need to have a bit line contact per cell) reducing the cost. However, it also reduces the speed of the NAND flash as well as increases the error potential; if something goes wrong with one cell it can become impossible to get information in and out of a whole row.

optoelectronics--a type of semiconductor chip/device, not an integrated circuit, that deals with converting light to electronic energy and vice versa.


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PLD (programmable logic device)--an integrated circuit that can be programmed to perform complex logic functions.

PMOS--a type of MOS transistor (see definition of MOS above) in which the electrical current comes from the flow of positive charges (hence the “P” in PMOS).

qualification–(1) qualification of a machine in a semiconductor fab refers to the process of installing the machine and running tests on the machine to confirm that it can reliably process semiconductor wafers. Qualification of a machine may take several weeks. (2) qualification of a new semiconductor fab or manufacturing line refers to running tests on the entire factory or manufacturing line to confirm that the factory can reliably processor semiconductor wafers. This can take several months. (3) qualification of a new process (often in a new factory) refers to running test on chips made using the new process to confirm that these chips are good chips and chips made on this process will reliably last a certain minimum time. It can take several quarters to years to develop a new process and several months to qualify the process.

RAM (random access memory)--a semiconductor memory in which the information can be retrieved in from any memory cell without looking through all the other memory cells. DRAM and SRAM are random access. NOR flash is random access, but NAND flash is serial access. For a NAND memory, all the cells in a whole line (a row) must be looked at one after the other.

Random Access Memory (RAM)–see RAM

semiconductor--a material that is neither a good conductor nor a good insulator, but can exhibit both properties. The most commonly used semiconductor material is silicon.

sensor--a chip/device that can sense heat, light, or pressure and generate a corresponding signal that can be measured or interpreted.

single-level cell (SLC)--as opposed to a multilevel cell, a single-level cell is a NAND memory cell that can store just one memory bit (a 1 or a 0) at a time.

SLC--see single-level cell.

Solid-state drive (SSD)--a form of computer memory, replacement for a hard disk drive, made of NAND flash memory.

spot price, spot market--semiconductor memory can be bought on contract, in which prices are negotiated in advance, twice per month, or on the spot market which offers a constantly changing price. The bulk of DRAM is sold on contract, but the spot market is often thought to be a leading indicator of contract pricing.

SDRAM--synchronous DRAM, not to be confused with SRAM. A type of DRAM. SDRAM was used in the 1990s, but in the past two years DDR has become the standard type of DRAM.

SRAM (static random access memory)--type of volatile memory that is generally faster and more reliable than DRAM due to the fact that it does not have to be refreshed like DRAM. It is generally more expensive and is commonly used as cache memory in a computer.

standard linear--standard analog chips for doing generic tasks (as opposed to applications-specific functions), general sold through catalogs.

stepper–see lithography tool.

synchronous--many chips are synchronous in operation, which means that a clock signal needs to be generated and all calculations or other operations in the circuit wait for the next beat of the clock before they happen. This makes sure that signals are transferred at the same time, avoiding errors that may occur as a result of one thing happening earlier than something else. The higher the clock frequency, the more things that can happen per second, and the more the chip can achieve. Typical clock frequencies are 100s of megahertz (hundreds of million times per second) or several gigahertz (several billion times per second).

transistor--a basic building block of integrated circuits generally working as a switch (turning on or off the flow of electrons) or as an amplifier (making a small voltage bigger). The term transistor comes from the concept of trans-resistance, being able to influence a current in one place by a current or a voltage in another place. The first transistors were not semiconductor transistors at all, but vacuum tubes.


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Tri-Gate–Tri-Gate is Intel’s name for its 3D transistors. In a 3-D transistor the gate wraps around the channel. Since the gate is controlling the channel from three sides (hence the alternative name, tri gate) it can turn-on the current more strongly (increasing the performance) or shut off the current more completely (reducing the power consumption associated with leakage). A 3-D transition is sometimes called a FinFET because the gate looks like a fin. “FET” stands for “field effect transistor.”

volatile memory--memory that loses its data when the power is turned off.

wafer--a round semiconductor disk, about half a millimeter thick, most commonly with a diameter of 8 or 12 inches, on which semiconductor circuitry is made. After a wafer has passed through the circuit fabrication process, it is cut up into squares, the semiconductor chips, each containing a circuit.

wafer capacity--the rate at which semiconductor wafers can be processed in a semiconductor fab, typically described in wafer starts per week or wafer starts per month (how many wafers begin being processed in a week or month).

wafer equivalent--Since the transition to different wafer sizes often takes place over the span of years, at any given point in time the semiconductor industry as a whole is doing its manufacturing on more than one size of wafer. A lot of manufacturing is done on 200mm (8 inch) and 300mm (12 inch) wafers, but there still remains some manufacturing on 6-inch and even some 5-,4- and 3-inch wafer processing. To normalize all these different wafer sizes, capacity numbers (and other things associated with wafers, such as, for example, prices charged per wafer by foundries) are often couched in “wafer equivalent” numbers. A 300mm wafer has 2.25x the area of a 200mm wafer, and hence, 2.25 more chips can be fabricated on such a wafer. Therefore, a 300mm wafer counts as 2.25 200mm wafers when adding up wafer capacity.

wafer starts, wafer output--semiconductor chip production can be measured in terms of wafer starts per week or wafer starts per month (how many wafers begin being processed in a week or month). An alternative measurement is wafer outs per week or wafer outs per month (how many wafers complete their process in a week or month.) Since it typically takes about 13 weeks to process a wafer, the time difference between wafer starts and wafer outs is about a quarter.

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SECURITIES: NOT FDIC-INSURED/NOT BANK-GUARANTEED/MAY LOSE VALUE

Sam J. Pearlstein Co-Head of Equity Research (212) 214-5054

[email protected]

Diane Schumaker-Krieg Global Head of Research, Economics & Strategy

(212) 214-5070 / (704) 410-1801 [email protected]

Todd M. Wickwire Co-Head of Equity Research (410) 625-6393

[email protected]

Paul Jeanne, CFA, CPA Associate Director of Research

(443) 263-6534 / (212) 214-8054 [email protected]

Lisa Hausner Global Head of Publishing

(443) 263-6522 [email protected]

CONSUMER

Beverage/Convenience Stores/Tobacco Bonnie Herzog (212) 214-5051

Jessica Gerberi, CFA (212) 214-5029 Adam Scott (212) 214-8064

Cosmetics, Household & Personal Care Chris Ferrara, CFA, CPA (212) 214-8050 Joe Lachky, CFA (314) 875-2042

Zachary Fadem, CPA (212) 214-8018 Education

Trace A. Urdan (415) 947-5470 Jeffrey Lee (415) 396-4328

Food John Baumgartner, CFA (212) 214-5015

Homebuilding/Building Products Adam Rudiger, CFA (617) 603-4260

Joey Matthews, CPA (415) 396-3873 Leisure

Timothy Conder, CPA (314) 875-2041 Karen Wang (314) 875-2556 Marc J. Torrente (314) 875-2557

Restaurants & Foodservice Jeff Farmer, CFA (617) 603-4314

Imran Ali (617) 603-4315 Retail

Paul Lejuez, CPA, CFA (212) 214-5072 Tracy Kogan (212) 214-8065 Justin C. Matthews (212) 214-8059

Matt Nemer (415) 396-3938 Omair Asif (415) 222-1159 Maren Kasper (415) 396-3194

Kate Wendt (415) 396-3977 Evren Kopelman, CFA (212) 214-8024

Connie Wang (212) 214-5024

ENERGY

Exploration & Production David R. Tameron (303) 863-6891 Gord0n Douthat, CFA (303) 863-6920

Brad Carpenter, CFA (303) 863-6894 Jamil Bhatti, CFA (303) 863-6880 Richard Vidal (303) 863-6816

Master Limited Partnerships Michael J. Blum (212) 214-5037 Sharon Lui, CPA (212) 214-5035 Praneeth Satish (212) 214-8056

Eric Shiu (212) 214-5038 Ned Baramov, CFA (212) 214-8021 David Freeland (212) 214-5050

Sam Dubinsky (212) 214-5043 Amir Chaudhri (212) 214-5045

Utilities Neil Kalton, CFA (314) 875-2051 Sarah Akers, CFA (314) 875-2040

Jonathan Reeder (314) 875-2052 Glen F. Pruitt (314) 875-2047 Peter Flynn (314) 875-2049

Oilfield Services and Drilling Matthew D. Conlan, CFA (212) 214-5044

Oilfield Services and Equipment Judson E. Bailey, CFA (713) 577-2514 Daniel Cruise (713) 577-2515 Coleman W. Sullivan, CFA (713) 577-2510

David Cheng (713) 577-2516

ENERGY – CONT.

Refiners & Integrateds Roger D. Read (713) 577-2542

Lauren Hendrix (713) 577-2543

FINANCIAL SERVICES

BDCs Jonathan Bock, CFA (443) 263-6410

Ronald Jewsikow (443) 263-6449 Gregory Nelson (704) 410-2197

Brokers/Exchanges/Asset Managers Christopher Harris, CFA (443) 263-6513

Andrew Bond (443) 263-6526 Robert Ryan, CFA (212) 214-5025

Insurance John Hall (212) 214-8032 Elyse Greenspan, CFA (212) 214-8031

Kenneth Hung, CFA, ASA (212) 214-8023 Rashmi H. Patel, CFA (212) 214-8034

Specialty Finance Joel J. Houck, CFA (443) 263-6521

Vivek Agrawal (443) 263-6563 Charles Nabhan (443) 263-6578 Max Maier (443) 263-6573

U.S. Banks Matt H. Burnell (212) 214-5030

Jason Harbes, CFA (212) 214-8068 Jared Shaw (212) 214-8028

Timur Braziler (212) 214-5048

HEALTH CARE

Biotechnology Brian C. Abrahams, M.D. (212) 214-8060 Matthew J. Andrews (617) 603-4218

Shin Kang, PhD (212) 214-5036 Ronald Hsu, M.D. (212) 214-5064

Healthcare Facilities Gary Lieberman, CFA (212) 214-8013

Ryan Halsted (212) 214-8022 Healthcare IT & Distribution

Jamie Stockton, CFA (901) 271-5551 Stephen Lynch (901) 271-5552 Nathan Weissman (901) 271-5553

Life Science Tools & Services Tim Evans (212) 214-8010

Luke E. Sergott (212) 214-8027 Managed Care

Peter H. Costa (617) 603-4222 Polly Sung, CFA (617) 603-4324 Brian Fitzgerald, CFA (617) 603-4277

Medical Technology Larry Biegelsen (212) 214-8015

Lei Huang (212) 214-8039 Craig W. Bijou (212) 214-8038 David Y. Brill. M.D. (212) 214-8042

Pharmaceuticals Michael Faerm (212) 214-8026

INDUSTRIAL

Aerospace & Defense Sam J. Pearlstein (212) 214-5054 Gary S. Liebowitz, CFA (212) 214-5055

Automotive/Electrical and Industrial Products Rich Kwas, CFA (410) 625-6370 David H. Lim (443) 263-6565

Deepa Raghavan, CFA (443) 263-6517 Chemicals

Frank J. Mitsch (212) 214-5022 Sabina Chatterjee (212) 214-8049

Containers & Packaging Chris Manuel (216) 643-2966

Gabe S. Hajde (216) 643-2967 Nikita V. Bely (216) 643-2968

Diversified Industrials Allison Poliniak-Cusic, CFA (212) 214-5062

Michael L. McGinn (212) 214-5052 Machinery

Andrew Casey (617) 603-4265 Justin Ward (617) 603-4268

Sara Magers, CFA (617) 603-4270 Metals & Mining

Sam Dubinsky (212) 214-5043 Amir Chaudhri (212) 214-5045

Shipping, Equipment Leasing, & Marine MLPs Michael Webber, CFA (212) 214-8019

Donald D. McLee (212) 214-8029 Transportation

Casey S. Deak (443) 263-6579

MEDIA & TELECOMMUNICATIONS

Advertising Peter Stabler (415) 396-4478

Steve Cho (415) 396-6056

Media & Cable Marci Ryvicker, CFA, CPA (212) 214-5010 Eric Katz (212) 214-5011

Stephan Bisson (212) 214-8033 John Huh (212) 2148044

Satellite Communications Andrew Spinola (212) 214-5012

Telecommunication Services - Wireless/Wireline Jennifer M. Fritzsche (312) 920-3548

Caleb Stein (312) 845-9797

REAL ESTATE, GAMING & LODGING

Gaming Cameron McKnight (212) 214-5046

Rich Cummings (212) 214-8030 Tiffany Lee (212) 214-8066

Healthcare/Manufactured Housing/Self Storage Todd Stender (562) 637-1371

Philip DeFelice, CFA (443) 263-6442 Jason S. Belcher (443) 462-7354

Lodging/Multifamily/Retail Jeffrey J. Donnelly, CFA (617) 603-4262

Dori Kesten (617) 603-4233 Robert LaQuaglia, CFA, CMT (617) 603-4263 Tamara Fique (443) 263-6568

Office/Industrial/Infrastructure Brendan Maiorana, CFA (443) 263-6516

Young Ku, CFA (443) 263-6564 Blaine Heck, CFA (443) 263-6529

TECHNOLOGY & SERVICES

Applied Technologies Andrew Spinola (212) 214-5012

Communication Technology Jess Lubert, CFA (212) 214-5013

Michael Kerlan (212) 214-8052 Gray Powell, CFA (212) 214-8048

Priya Parasuraman (617) 603-4269 E-commerce

Matt Nemer (415) 396-3938 Trisha Dill, CFA (312) 920-3594

Information & Business Services William A. Warmington, Jr. (617) 603-4283

Bill DiJohnson (617) 603-4271 Internet

Peter Stabler (415) 396-4478 Ignatius Njoku (415) 396-4064 Steve Cho (415) 396-6056

IT & BPO Services Ed Caso, CFA (443) 263-6524

Richard Eskelsen, CFA (410) 625-6381 Tyler Scott (443) 263-6540

IT Hardware Maynard Um (212) 214-8008

Munjal Shah (212) 214-8061 Santosh Sankar (212) 214-8007

Semiconductors David Wong, CFA, PhD (212) 214-5007

Amit Chanda (314) 875-2045 Parker Paulin (212) 214-5066

Software/Internet, Technology Jason Maynard (415) 947-5472

Karen Russillo (415) 396-3505 Vilma Chuy (415) 396-3345

Transaction Processing Timothy W. Willi (314) 875-2044

Robert Hammel (314) 875-2053 Alan Donatiello, CFA (314) 875-2054

STRATEGY

Equity Strategy Gina Martin Adams, CFA, CMT (212) 214-8043

Peter Chung (212) 214-8063 Strategic Indexing

Daniel A. Forth (704) 410-3233

ECONOMICS

Economists John E. Silvia, PhD (704) 410-3275 Mark Vitner (704) 410-3277 Jay H. Bryson, PhD (704) 410-3274 Eugenio J. Alemán, PhD (704) 410-3273 Sam Bullard (704) 410-3280 Anika Khan (704) 410-3271

RETAIL RESEARCH MARKETING

Retail Research Marketing Colleen Hansen (410) 625-6378

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October 22, 2014

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