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Chapter4-SMP - CSCI 211 Computer System Architecture Lec 8...

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CSCI 211 Computer System Architecture Lec 8 – Multiprocessor Introduction Xiuzhen Cheng Department of Computer Sciences The George Washington University Adapted from the slides by Dr. David Patterson @ UC Berkeley
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08/24/10 Csci 211 – Lecture 8 2 Outline MP Motivation SISD v. SIMD v. MIMD Centralized vs. Distributed Memory Challenges to Parallel Programming Consistency, Coherency, Write Serialization Write Invalidate Protocol Example Performance of SMP Conclusion
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08/24/10 Csci 211 – Lecture 8 3 1 10 100 1000 10000 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 Performance (vs. VAX-11/780) 25%/year 52%/year 20%/year Uniprocessor Performance (SPECint) VAX : 25%/year 1978 to 1986 RISC + x86: 52%/year 1986 to 2002 RISC + x86: 20%/year 2002 to present From Hennessy and Patterson, Computer Architecture: A Quantitative Approach , 4th edition, 2006 3X
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08/24/10 Csci 211 – Lecture 8 4 Déjà vu all over again? “… today’s processors … are nearing an impasse as technologies approach the speed of light..” David Mitchell, The Transputer: The Time Is Now ( 1989 ) Transputer (concurrent computing microprocessor) had bad timing (Uniprocessor performance ) Procrastination rewarded: 2X seq. perf. / 1.5 years “We are dedicating all of our future product development to multicore designs. … This is a sea change in computing” Paul Otellini, President, Intel ( 2005 ) All microprocessor companies switch to MP (2X CPUs / 2 yrs) Procrastination penalized: 2X sequential perf. / 5 yrs Manufacturer/Year AMD/’05 Intel/’06 IBM/’04 Sun/’05 Processors/chip 2 2 2 8 Threads/Processor 1 2 2 4 Threads/chip 2 4 4 32
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08/24/10 Csci 211 – Lecture 8 5 Other Factors Multiprocessors Growth in data-intensive applications Data bases, file servers, … Growing interest in servers, server perf. Increasing desktop perf. less important Outside of graphics Improved understanding in how to use multiprocessors effectively Especially server where significant natural TLP Advantage of leveraging design investment by replication Rather than unique design
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08/24/10 Csci 211 – Lecture 8 6 Flynn’s Taxonomy Flynn classified by data and control streams in 1966 SIMD Data Level Parallelism MIMD Thread Level Parallelism MIMD popular because Flexible: N pgms and 1 multithreaded pgm Cost-effective: same MPU in desktop & MIMD Single Instruction Single Data (SISD) (Uniprocessor) Single Instruction Multiple Data SIMD (single PC: Vector, CM-2) Multiple Instruction Single Data (MISD) (????) Multiple Instruction Multiple Data MIMD (Clusters, SMP servers) M.J. Flynn, "Very High-Speed Computers", Proc. of the IEEE , V 54, 1900-1909, Dec. 1966.
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08/24/10 Csci 211 – Lecture 8 7 Back to Basics “A parallel computer is a collection of processing elements that cooperate and communicate to solve large problems fast.” Parallel Architecture = Computer Architecture + Communication Architecture 2 classes of multiprocessors WRT memory: 1. Centralized Memory Multiprocessor < few dozen processor chips (and < 100 cores) in 2006
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