Innovating in aPost Moore’s Law World

Mark HorowitzEE & CS, Stanford University

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Mark Horowitz

• Yahoo! Professor, Stanford▶ Electrical Engineering & Computer Science▶ Ph.D. in EE from Stanford, 1984▶ Former EE Chair

• Research: Digital systems design▶ RISC machines - MIPS-X, TORCH▶ Distributed Shared Memory – FLASH, SMASH▶ High-speed IO – Rambus▶ Security – XOM▶ Computational Photography – Frankencamera▶ Extremely Efficient Computing – Darkroom, CE

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IT World is Changing

• Moving from technology to application driven▶ Success is no longer about access to latest technology▶ It is about finding the right application to address

• To understand why, we need to look at history▶ Why are computers so prevalent?

• How to be successful in this new age

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Moore’s Law Made Gates Cheap

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Dennard’s Scaling Made Them Fast & Low Energy

• The triple play:▶ Get more gates, 1/L2 1/2

▶ Gates get faster, CV/i ▶ Energy per switch CV2 3

Dennard, JSSC, pp. 256‐268, Oct. 19745

Our Expectation

• Cray-1: world’s fastest computer 1976-1982▶ 64Mb memory (50ns cycle time)▶ 40Kb register (6ns cycle time)▶ ~1 million gates (4/5 input NAND)▶ 80MHz clock▶ 115kW

• In 45nm (30 years later)▶ < 3 mm2

▶ > 1 GHz▶ ~ 1 W

CRAY‐16

Houston, We Have A Problem

http://cpudb.stanford.edu/ 7

The Power Limit

http://cpudb.stanford.edu/

Watts/m

m2

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We Were Greedy

10x too large

http://cpudb.stanford.edu/ 9

This Problem Is Not Going Away:P = C * Vdd2 * f

http://cpudb.stanford.edu/

L0.6

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Think About It

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Stagnation of Multi-Core Processors

http://cpudb.stanford.edu/12

Technology to the Rescue?

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Problems w/ Replacing CMOS

• Pretty fundamental physics▶ Avoiding this problem will be hard

• Its capability is pretty amazing▶ fJ/gate, 10ps delays, 109 working devices

e‐

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Catch - 22

Capital you need

Investment Risk

Very Different = High Risk

Build

ing Co

mpu

ters = Large $

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The Truth About Innovation

• Start by creating new markets 16

It is the End of Scaling, Not Silicon

• Silicon will not disappear▶ It will still be a huge business, but will consolidate▶ Growth rate is slower, and scaling is slow

• Silicon will become like concrete and steel▶ Basis of a huge industry, critical to everything▶ But fairly stable and predictable

• Will remain the dominate substrate for computing

Have A Shiny Ball, Now What?

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Cup Holders

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• Small additions to a complex product– With large perceived value

CPU Cup HoldersSpecialized Hardware

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A8

Consumer Cup Holders

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Improved Cup Holders (IoT)

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• Add communication to compute

From Bill Curtis Arm

Our CMOS Future

• Cup holders made for computing devices▶ Need to optimize energy efficiency for high performance systems▶ Build specialized hardware for that application

• Cup holders made from computing devices▶ Capability of today’s technology is incredible▶ Can add computing and communication for nearly $0▶ Key questions are what problems need to be solved?

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What This Means

• Computer performance scaling will slow

• Computing chips for specific markets will appear▶ And manufacturing the addition secret sauce won’t cost very much

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Computing platforms are stabilizing

The New Challenge:

• Application specific products have smaller markets▶ Harder to predict what will win; most will fail▶ Wins on average are smaller

• People who have product ideas▶ Don’t know about hardware, let alone know how to use it

• People who know about the technology▶ Are a special subset of the population▶ May not be in touch with what great products will be

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And System Design Is Hard

• Every look at a modern SoC “datasheet”?▶ They are 500+ pages, and many types

• And then you have to worry about the OS▶ And the drivers

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The Problem: Last of Clarke’s Three Laws

• When a distinguished but elderly scientist states that something is possible, he is almost certainly right. When he states that something is impossible, he is probably wrong.

• The only way of discovering the limits of the possible is to venture a little way past them into the impossible.

• Any sufficiently advanced technology is indistinguishable from magic.

E40M Fall 2015 Lecture 1

Remember This Trade-off?

Personal cost (time/money)

Product Risk

• Need to reduce cost to play▶ Building constructors, not

instances

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Needed Infrastructure

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• Apps developers need to work in their space▶ Program input; auto generate the hardware and system software

• Hardware prototypes shipped▶ Knowledge of fabrication sources▶ Debugging / bring up support

• Sales channel for finished devices▶ To encourage more people to spend time creating new apps

Tock Operating System• Traditionally, embedded systems assume all code

is trusted►No memory protection►No privilege levels

• IoT is moving towards an application store model►Pebble watch►iWatch

• Need an embedded operating system that supports running multiple, untrusted applications

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Ravel Framework• Write a data processing pipeline

►Consists of a set of Models, describing data as it is stored►Transforms move data between Models►Instances of Models are bound to devices►Views can display Models►Controllers determine how data moves to Transforms

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Key to Success

System needs to appeal to two sets of users

• Application designers who want to use the system▶ Need the system to be able to handle many details for them

• Expert designers who want to extend the system▶ Would like it to be “simple” to add new stuff

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Recently Things Are Looking Up

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A New Hope

• If killer products are going to be application driven▶ Application experts need to design them

• If technology is scaling more slowly▶ We can incorporate current design knowledge into tools▶ To create extensible system constructors

• We can leverage the 2nd bullet to enable the 1st

▶ To usher in a new wave of innovative computing products

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