CSE502_lec16+17+18-SMPS10

CSE502_lec16+17+18-SMPS10 - CSE 502 Graduate Computer...

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Unformatted text preview: CSE 502 Graduate Computer Architecture Lec 16-18 – Symmetric MultiProcessing Larry Wittie Computer Science, StonyBrook University http://www.cs.sunysb.edu/~cse502 and ~lw Slides adapted from David Patterson, UC-Berkeley cs252-s06 4/5-12/10 CSE502-S10, Lec 16-18-SMP 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 • Conclusion • Reading Assignment: Chapter 4 MultiProcessors 4/5-12/10 CSE502-S10, Lec 16-18-SMP 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 ??%/year Uniprocessor Performance (SPECint) • VAX : 25%/year 1978 to 1986 • RISC + x86: 52%/year 1986 to 2002; ??%/year 2002 to present From Hennessy and Patterson, Computer Architecture: A Quantitative Approach , 4th edition, 2006 3X 4/5-12/10 CSE502-S10, Lec 16-18-SMP 4 Déjà vu, again? Every 10 yrs, parallelism: key! “… today’s processors … are nearing an impasse as technologies approach the speed of light..” David Mitchell, The Transputer: The Time Is Now ( 1989 ) • Transputer had bad timing (Uniprocessor performance ↑ in 1990s) ⇒ In 1990s, 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) ⇒ Now, procrastination penalized: sequential performance - only 2X / 5 yrs Manufacturer/Year AMD/’05 Intel/’06 IBM/’04 Sun/’05 Sun/’07 Processors/chip 2 2 2 8 8 Threads/Processor 1 2 2 4 8 Threads/chip 2 4 4 32 64 4/5-12/10 CSE502-S10, Lec 16-18-SMP 5 Other Factors ⇒ Multiprocessors Work Well • Growth in data-intensive applications – Data bases, file servers, web servers, … (All: many separate tasks) • Growing interest in servers, server performance • Increasing desktop performance less important – Outside of graphics • Improved understanding in how to use multiprocessors effectively – Especially servers, where significant natural TLP (separate tasks) • Huge cost $$$ advantage of leveraging design investment by replication – Rather than unique designs for each higher performance chip (a fast new design costs billions of dollars in R&D and factories) 4/5-12/10 CSE502-S10, Lec 16-18-SMP 6 Flynn’s Taxonomy • Flynn classified by data and control streams in 1966 • SIMD ⇒ Data Level Parallelism (problem: locked step) • MIMD ⇒ Thread Level Parallelism (independent steps) • MIMD popular because – Flexible: N programs or 1 multithreaded program – Cost-effective: same MicroProcUnit in desktop PC & MIMD Single Instruction Stream, Single Data Stream ( SISD ) ( Uniprocessors ) Single Instruction Stream, Multiple Data Stream SIMD (Single ProgCtr: CM-2)...
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This note was uploaded on 11/06/2010 for the course CSE 502 taught by Professor Wittie,l during the Spring '08 term at SUNY Stony Brook.

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CSE502_lec16+17+18-SMPS10 - CSE 502 Graduate Computer...

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