ece 462/562 computer architecture and design t-th 12:30-1:45 in harv210 ece462 instructor name:ali...
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ECE 462/562 Computer Architecture and Design T-Th 12:30-1:45 in HARV210www.ece.arizona.edu/~ece462
Instructor
Name: Ali Akoglu (ece.arizona.edu/~akoglu)
Office: ECE 356-B
Phone: (520) 626-5149
Email: akoglu@ece.arizona.edu
Office Hours: Tuesdays 11:00 AM – 12:00 PMThursdays 11:00 AM- 12:00 AM or by appointment
Computer Architecture
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Algorithm
Gates/Register-Transfer Level (RTL)
Application
Instruction Set Architecture (ISA)
Operating System/Virtual Machines
Devices
Programming Language
Circuits
Physics
Abstraction Layers
3
Computer Architecture is Design and Analysis
Design
Analysis
Architecture is an iterative process:• Searching the space of possible designs• At all levels of computer systems
Creativity
Good IdeasGood Ideas
Mediocre IdeasBad Ideas
Cost /PerformanceAnalysis
Computer Architecture
4
Compatibility
Cost of software development makes compatibility a major force in market
Applications
Technology
Applications suggest how to improve technology, provide revenue to fund development
Improved technologies make new applications possible
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Trends: The End of the Uniprocessor Era
Intel cancelled high performance uniprocessor, joined IBM and Sun for multiple processors
Intel cancelled high performance uniprocessor, joined IBM and Sun for multiple processors
Hardware based
Hardware
and softw
are, ILP!
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• Old Conventional Wisdom: Power is free, Transistors expensive
• New Conventional Wisdom: “Power wall” Power expensive, Xtors free (Can put more on chip than can afford to turn on)
• Old CW: Sufficiently increasing Instruction Level Parallelism via compilers, innovation (Out-of-order, speculation, VLIW, …)
• New CW: “ILP wall” law of diminishing returns on more HW for ILP
• Old CW: Multiplies are slow, Memory access is fast
• New CW: “Memory wall” Memory slow, multiplies fast (200 clock cycles to DRAM memory, 4 clocks for multiply)
• Old CW: Uniprocessor performance 2X / 1.5 yrs
• New CW: Power Wall + ILP Wall + Memory Wall = Brick Wall• Uniprocessor performance now 2X / 5(?) yrs
• Sea change in chip design: multiple “cores” (2X processors per chip / ~ 2 years)
• More simpler processors are more power efficient
Crossroads: Conventional Wisdom
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Instruction Set Architecture: Critical Interface
instruction set
software
hardware
• Properties of a good abstraction– Lasts through many generations (portability)– Used in many different ways (generality)– Provides convenient functionality to higher levels– Permits an efficient implementation at lower levels
8
ISA vs. Computer Architecture
• Old definition of computer architecture = instruction set design
• Other aspects of computer design called implementation
• Our view is computer architecture >> ISA
• Architect’s job much more than instruction set design; technical hurdles today more challenging than those in instruction set design
• What really matters is the functioning of the complete system
– hardware, runtime system, compiler, operating system, and application
• Computer architecture is not just about transistors, individual instructions, or particular implementations
9
Course Focus
Understanding the design techniques, machine structures, Understanding the design techniques, machine structures, technology factors, evaluation methods that will determine technology factors, evaluation methods that will determine the form of computers in 21st Centurythe form of computers in 21st Century
Technology ProgrammingLanguages
OperatingSystems History
Applications Interface Design(ISA)
Measurement & Evaluation
Parallelism
Computer Architecture:• Organization• Hardware/Software Boundary Compilers
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Related Courses
ECE369ECE369 ECE462/562
ECE462/562
ECE568ECE568
ECE474/574
ECE474/574
Basic computer organization, first look at pipelines + caches
Computer Architecture, First look at parallel
architectures
Parallel Processing
Computer Aided Logic Design, FPGAs
Strong
Prerequisite
ECE 576ECE 576
Computer Based Systems
ECE569ECE569
High Performance Computing, Advanced
Topics
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Introduction
• Text for ECE462/562: Hennessy and Patterson’s Computer Architecture, A Quantitative Approach, 5th Edition
• Topics1. Simple machine design (ISAs, microprogramming,
unpipelined machines, Iron Law, simple pipelines)2. Memory hierarchy (DRAM, caches, optimizations) plus
virtual memory systems, exceptions, interrupts3. Complex pipelining (score-boarding, out-of-order issue)4. Explicitly parallel processors (vector machines, VLIW
machines, multithreaded machines)5. Multiprocessor architectures (memory models, cache
coherence, synchronization)
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Your ECE462/562
•How would you like your ECE462/562?•Mix of lecture vs. discussion•Depends on how well reading is done before class•Goal is to learn how to do good systems research
•Learn a lot from looking at good work in the past•At commit point, you may chose to pursue your own new idea instead.
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Coping with ECE462/562
• Undergrads must have taken ECE274 and ECE369• Grad students with too varied background
• Review Appendix A, B, C• review of ISA, Datapath, Pipelining and Memory
Hierarchy
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Policies
• Background: ECE369 or equivalent, based on Patterson and Hennessy’s Computer Organization and Design•Prerequisite: ECE274 & ECE369 & Programming in C•3 to 4 assignments, 2 exams, final project•Grad students: extra exam questions, survey paper and presentation•NO LATE ASSIGNMENTS•Make-ups may be arranged prior to the scheduled activity. •Inquiries about graded material => within 3 days of receiving a grade. •You are encouraged to discuss the assignment specifications with your instructor, and your fellow students. However, anything you submit for grading must be unique and should NOT be a duplicate of another source. •Read before the class•Participate and ask questions•Manage your time•Start working on assignments early
Grading
Distribution of Components Grades Scale
Component Percentage Percentage Grade
Assignments+Quiz+Participation
35 90-100% A
Exam-I 15 80-89% B
Exam-II 15 70-79% C
Project 35 60-69% D
Total 100 Below 60% E
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Introduction
•Assignments and Project Pairs only Who is my partner? (email by 09/06)
• Assignment-0 due 08/28
• Announcements on the web
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Research Paper Reading
• As graduate students, you are now researchers• Most information of importance to you will be
in research papers• Ability to rapidly scan and understand research
papers is key to your success
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Project (Undergrad vs Grad)
• Transition from undergrad to grad student• ECE wants you to succeed, but you need to show
initiative• pick topic (more on this later)• meet 3 times with faculty to see progress• give oral presentation (grad students only)• written report like conference paper• 3 weeks work full time for 2 people• Opportunity to do “research in the small” to help make
transition from good student to research colleague
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Project (Undergrad vs Grad)
• Recreate results from research paper to see• If they are reproducible• If they still hold• Papers from ISCA, HPCA, MICRO, IPDPS, ISC
• Performance evaluation of an architecture• Using industry sponsored tools
• GEM5: gem5.org• Pin: pintool.org• SimpleScalar: simplescalar.com
• A complete end-to-end processor (UGs !!)• Take advantage of FPGAs!!
• Propose your own research project that is related to computer architecture
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Measuring Performance
• Topics: (Chapter 1)
Technology trendsPerformance equations
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Technology Trends and This Book
20091996When I took this class!
2002 2011Shift to multicore!Reduced emphasis on ILPIntroduce thread level P.
Reduced ILP to 1 chapter!
Request, Data, Thread, Instruction Level
Introduce: GPU, cloud computing, Smart phones, tablets!
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Problems
• Algorithms, Programming Languages, Compilers, Operating Systems, Architectures, Libraries, … not ready to supply Thread Level Parallelism or Data Level Parallelism for 1000 CPUs / chip,
• Architectures not ready for 1000 CPUs / chip• Unlike Instruction Level Parallelism, cannot be
solved by just by computer architects and compiler writers alone, but also cannot be solved without participation of computer architects
• 5th Edition Computer Architecture: A Quantitative Approach explores shift from Instruction Level Parallelism to Thread Level Parallelism / Data Level Parallelism
23
Classes of Parallelism
• In Applications Data Level Parallelism
o Data items that can be operated on concurrently Task-level Parallelism
o Tasks of a work can operate independently • In Hardware
ILP: exploits DLP with compiler, pipelining, speculative execution
Vector Architectures and GPUs: exploit DLP by applying a single instruction to a collection of data
Thread-level parallelism: exploits DLP and TLP, tightly coupled hardware, interaction among threads
Request level parallelism: exploits largely decoupled tasks specified by the programmer
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Processor Technology Trends
• Shrinking of transistor sizes: 250nm (1997) 130nm (2002) 65nm (2007) 32nm (2010) 28nm(2011, AMD GPU, Xilinx FPGA) 22nm(2011, Intel Ivy Bridge, die shrink of the Sandy Bridge architecture)
• Transistor density increases by 35% per year and die size increases by 10-20% per year… more cores!
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Trends: Historical Perspective
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Power Consumption Trends
• Dyn power activity x capacitance x voltage2 x frequency
• Capacitance per transistor and voltage are decreasing, but number of transistors is increasing at a faster rate; hence clock frequency must be kept steady
• Leakage power is also rising
• Power consumption is already between 100-150W in high-performance processors today
3.3GHz Intel core i7: 130 watts
27
Recent Microprocessor Trends
2004 2010
Source: Micron University Symp.
Transistors: 1.43x / year
Cores: 1.2 - 1.4x
Performance: 1.15x
Frequency: 1.05x
Power: 1.04x
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Improving Energy Efficiency Despite Flat Clock Rate
•Turn off the clock of inactive modules• Disable FP unit, core, etc.
•Dynamic Voltage-Frequency Scaling• Periods of low activity, lower the clock rate
•Low power mode• DRAMs lower power mode for extending the battery
•Overclocking• Intel, Turbo mode (2008), chip decides safe clock rate • i7 3.3 GHz, can run in short bursts for 3.6GHz
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Modern Processor Today
• Intel Core i7
Clock frequency: 3.2 – 3.33 GHz 45nm and 32nm products Cores: 4 – 6 Power: 95 – 130 W Two threads per core 3-level cache, 12 MB L3 cache Price: $300 - $1000
30
Other Technology Trends
• DRAM density increases by 40-60% per year, latency has reduced by 33% in 10 years, bandwidth improves twice as fast as latency decreases
• Disk density improves by 100% every year, latency improvement similar to DRAM
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First Microprocessor Intel 4004, 1971
• 4-bit accumulator architecture
• 8m pMOS
• 2,300 transistors
• 3 x 4 mm2
• 750kHz clock
• 8-16 cycles/inst.
32[ Personal Computing Ad, 11/81]
Hardware•Team from IBM building PC prototypes in 1979•Motorola 68000 chosen initially, but 68000 was late•8088 is 8-bit bus version of 8086 => allows cheaper system•Estimated sales of 250,000•100,000,000s sold
33
• Carried in two tractor trailers, 12 tons + 8 tons
• Built for US Army Signal Corps
DYSEAC, first mobile computer!
34
Measuring Performance
• Two primary metrics: wall clock time (response time for a program) and throughput (jobs performed in unit time)
• To optimize throughput, must ensure that there is minimal waste of resources
• Performance is measured with benchmark suites: a collection of programs that are likely relevant to the user
SPEC CPU 2006: cpu-oriented programs (for desktops) SPECweb, TPC: throughput-oriented (for servers) EEMBC: for embedded processors/workloads
35
Performance
CPU time = Seconds = Instructions x Cycles x Seconds
Program Program Instruction Cycle
CPU time = Seconds = Instructions x Cycles x Seconds
Program Program Instruction Cycle Inst Count CPI Clock Rate
Program X
Compiler X X
Inst. Set. X X
Organization X X
Technology X
36
Amdahl’s Law
• Architecture design is very bottleneck-driven – make the common case fast, do not waste resources on a component that has little impact on overall performance/power
• Amdahl’s Law: performance improvements through an enhancement is limited by the fraction of time the enhancement comes into play
37
Amdahl’s Law
• Considering an enhancement that runs 10 times faster than the original machine but is only usable 40% of the time. • Only 1.56x overall speedup
• An application is “almost all” parallel: 90%. Speedup using • 10 processors => 5.3x• 100 processors => 9.1x• 1000 processors => 9.9x
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Principle of Locality
• Most programs are predictable in terms of instructions executed and data accessed
• Temporal locality: a program will shortly re-visit X
• Spatial locality: a program will shortly visit X+1
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Exploit Parallelism
• Most operations do not depend on each other – hence, execute them in parallel
• At the circuit level, simultaneously access multiple ways of a set-associative cache
• At the organization level, execute multiple instructions at the same time
• At the system level, execute a different program while one is waiting on I/O
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