1 / 20

CS/ECE 3330 Computer Architecture

CS/ECE 3330 Computer Architecture. Chapter 1 Performance / Power. Last Time. Overview of computer architecture Low-level software High-level hardware The interface between the two (ISA) What’s new and cool Multicore and heterogeneity Power, temperature, reliability Logistics

holt
Download Presentation

CS/ECE 3330 Computer Architecture

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. CS/ECE 3330Computer Architecture Chapter 1 Performance / Power

  2. Last Time • Overview of computer architecture • Low-level software • High-level hardware • The interface between the two (ISA) • What’s new and cool • Multicore and heterogeneity • Power, temperature, reliability • Logistics • Ben Kreuter brk7bx@virginia.edu Wed 7PM • Michelle McDaniel mm4ab@virginia.edu Thu 3PM

  3. Class Survey • What does it mean to have better performance?

  4. Defining Performance • Which airplane has the best performance?

  5. Response Time and Throughput • Response time (execution time) • How long it takes to do a task • Throughput (bandwidth) • Total work done per unit time • e.g., tasks/transactions/… per hour • How are response time and throughput affected • By replacing the processor with a faster version? • By adding more processors? • We’ll focus on response time for now…

  6. Relative Performance • Define Performance = 1/Execution Time • “X is n time faster than Y” • Example: time taken to run a program • 20s on A, 30s on B • So A is times faster than B • Execution TimeB / Execution TimeA= 30s / 20s = 1.5 • 1.5

  7. Measuring Execution Time • Elapsed time • Total response time, including all aspects • Processing, I/O, OS overhead, idle time • Determines system performance • CPU time • Time spent processing a given job • Discounts I/O time, other jobs’ shares • Comprises user CPU time and system CPU time • Different programs are affected differently by CPU and system performance

  8. CPU Clocking • Operation of digital hardware governed by a constant-rate clock Clock period Clock (cycles) Data transferand computation Update state • Clock period: duration of a clock cycle • e.g., 250ps = 0.25ns = 250×10–12s • Clock frequency (rate): cycles per second • e.g., 4.0GHz = 4000MHz = 4.0×109Hz

  9. CPU Time • Performance improved by • Reducing number of clock cycles • Increasing clock rate • Hardware designer must often trade off clock rate against cycle count

  10. CPU Time Example • Computer A: 2GHz clock, 20s CPU time • Designing Computer B • Aim for 12s CPU time • Can do faster clock, but causes 1.2 × clock cycles • How fast must Computer B’s clock be?

  11. Instruction Count and CPI • Instruction Count for a program • Determined by program, ISA and compiler • Average cycles per instruction • Determined by CPU hardware • If different instructions have different CPI • Average CPI affected by instruction mix

  12. CPI Example • Computer A: Cycle Time = 300ps, CPI = 2.0 • Computer B: Cycle Time = 600ps, CPI = 1.4 • Same ISA • Which is faster, and by how much? A is faster… …by this much

  13. CPI in More Detail • If different instruction classes take different numbers of cycles • Weighted average CPI Relative frequency

  14. CPI Example • Alternative compiled code sequences using instructions in classes A, B, C • Sequence 1: IC = 10 • Clock Cycles= 4×1 + 2×2 + 4×3= 20 • Avg CPI= 20/10 = 2.0 • Sequence 2: IC =12 • Clock Cycles= 8×1 + 2×2 + 2×3= 18 • Avg CPI= 18/12 = 1.5

  15. The Big Picture • Performance depends on • Algorithm: affects IC, possibly CPI • Programming language: affects IC, CPI • Compiler: affects IC, CPI • Instruction set architecture: affects IC, CPI, Tc

  16. Pitfall: Amdahl’s Law • Improving an aspect of a computer and expecting a proportional improvement in overall performance • Example: multiply accounts for 80s/100s • How much improvement in multiply performance to get 5× overall? • Can’t be done! • Corollary: make the common case fast

  17. Benchmarking • Real applications • Modified applications • Kernels (small, critical parts of real applications) • Toy benchmarks • Synthetic benchmarks + Accuracy -

  18. SPEC CPU Benchmarks • Programs used to measure performance • Supposedly typical of actual workload • Standard Performance Evaluation Corp (SPEC) • Develops benchmarks for CPU, I/O, Web, … • SPEC CPU2006 • Elapsed time to execute a selection of programs • Negligible I/O, so focuses on CPU performance • Normalize relative to reference machine • Summarize as geometric mean of performance ratios • CINT2006 (integer) and CFP2006 (floating-point)

  19. CINT2006 for Opteron X4 2356 High cache miss rates

  20. Summary • Performance can be measured a number of ways • Know the ways, and the potential misconceptions • Mostly boils down to the “standard performance equation” • Next Time… • Power has become a limiting factor • First problem set is due (2PM)

More Related