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CSC 4250 Computer Architectures

CSC 4250 Computer Architectures. August 29, 2006 Chap.1. Fundamentals of Computer Design. What you will learn in this class. Quantitative approach Instruction set principles Floating-point number and arithmetic Basic pipelining Advanced pipelining Caches Virtual memory. Syllabus.

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CSC 4250 Computer Architectures

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  1. CSC 4250Computer Architectures August 29, 2006Chap.1. Fundamentals of Computer Design

  2. What you will learn in this class • Quantitative approach • Instruction set principles • Floating-point number and arithmetic • Basic pipelining • Advanced pipelining • Caches • Virtual memory

  3. Syllabus • Chap. 1. Fundamentals of Computer Design • Chap. 2. Instruction Set Principles • Appx. H. Computer Arithmetic • Appx. A. Pipelining • Chap. 3. Instruction Level Parallelism: Hardware • Chap. 4. Instruction Level Parallelism: Software • Chap. 5. Memory Hierarchy

  4. How to determine your letter grade • Eleven homework assignments: 20% • Midterm 1: 20% • Midterm 2: 20% • Final exam: 40% • Cutoffs for A, B, and C: 90%, 80%, and 70% • Cutoffs may be lowered (it will not be raised) • So if your total exceeds 90%, you get an A.

  5. Homework 1 • Due in class next Tuesday, September 5 • Problems 1.1, 1.2, and 1.3 • Late penalty: 20% per weekday

  6. Important Dates • Midterm 1: Tuesday, October 3 • Fall break: October 7-9 • Midterm 2: Tuesday, November 7 • Thanksgiving: November 22-25 • Last day of this course: Friday, December 8 • Finals week: December 13-19

  7. History of Computers • Mechanical Era (1600’s – 1940’s) • Electronic Era (1945 – present)

  8. Mechanical Era • Pascal (1642) • Leibniz (1673) • Babbage (1822) • Boole (1847) • Hollerith (1889) • Zuse (1938) • Aiken (1943)

  9. Electronic Era • Generation 1 (1945 – 1958) • Vacuum tubes, von Neumann architecture • Generation 2 (1958 – 1964) • Transistors, HLL, core memory • Generation 3 (1964 – 1974) • ICs, semiconductor memory, micro and multi prog • Generation 4 (1974 – present) • LSI, VLSI, Mpp, PC; 32 years!

  10. Software/Internet Era? • 1980’s – present • UNIX – Sun Micro • Windows – Microsoft • Web browser – Netscape → AOL → TWX • E-commerce – Yahoo!, Amazon, eBay • Search engine – Google (newest villain?)

  11. Technology Trends • Transistor density up 35% per year • DRAM: • Density up 40-60% per year • Cycle time down 1/3 per decade • Cache design

  12. Discrete Leaps • 32 bit microprocessor early 1980’s • Level 1 cache on chip late 1980’s • Pentium 2 and Celeron • 486 – lawsuit on numbers

  13. Significant Technology Companies • Bell Lab • IBM • CDC • Cray → SGI • Xerox PARC • Mac, laser printer, 3Com, Adobe • DEC → Compaq → HP

  14. MIPS • What does MIPS stand for? • Machines with higher MIPS rate seem faster • Problem: • Compare machines with different instruction sets • ISA: instruction set architecture

  15. MIPS • Company founded by one author of textbook • Microprocessor without Interlocking Pipeline Stages

  16. MIPS Example • FP vs. SW routines for FP operations • FPU uses less time and fewer instructions • SW uses many simple integer instructions, leading to higher MIPS rate

  17. MFLOPS • Mega flop? • Similar difficulty: add/subtract, square root

  18. Performance Analysis • Real programs: Word • Kernels: Livermore loops, Linpack • Synthetic benchmarks: whetstone,dhrystone • Toy benchmarks: quicksort • SPEC – • System Performance Evaluation Corp

  19. SPECint Performance • VAX 11/780 in 1984 = 1

  20. Four Rules • CPU performance equation • Amdahl’s Law • Principle of locality • Price performance

  21. CPU Performance Equation • CPU time = IC × CPI × cct • IC: instruction count • Depends on ISA and compiler • CPI: cycles per instruction • Depends on ISA and pipelining • Cct: clock cycle time • Depends on hardware technology

  22. Two Supercomputers • Cray X-MP and Hitachi S810/20b • P1: A(i) = B(i) + C(i) + D(i) + E(i) vector length 1,000 done 100,000 times • P2: Vectorized FFT vector lengths 64, 32, 16, 8, 4, 2

  23. Amdahl’s Law • Speedup = Old time / New Time • Fraction of enhanced: f • Speedup of enhanced: S • Speedup = 1 / [ (1 − f) + f / S ]

  24. Examples • f = 0.2, S = 10 • → Speedup = 1.22 • f = 0.5, S = 1.6 • → Speedup = 1.23 • Consider MPP. Let f = 0.9 and S = 1,000,000 • What is bound on speedup?

  25. Principle of Locality • Program reuses data and instructions used recently • Program spends 90% execution time in 10% of code • Predict which instructions and data the program will use based on accesses in the past • → instruction and data caches, branch prediction

  26. Two Types of Locality • Temporal locality: • recently accessed items • Spatial locality: • items whose addresses are near

  27. Price Performance • MIPS rate of machine divided by its price • Are supercomputers competitive in terms of price performance? • Many applications need answers as quickly as possible, e.g., military, finance, and science

  28. Integer Performance & Price-Performance

  29. FP Performance & Price-Performance

  30. Embedded Processors: Performance

  31. Embedded Processors: Price Performance

  32. Embed. Processors: Performance per Watt

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