1. Power calculation for transistor operation What will cause power consumption to increase? CS2710 Computer Organization1

2. 2 Measuring the current used by the Atmega microprocessor shows a linear relationship Note: V=5v for in this case

3. CS2710 Computer Organization3 What effect does increasing voltage to a microprocessor have on power? On speed? Below around 2.5v (for this microprocessor), the transistors simply stop working

4. The Power Wall: Why haven’t clock rates continued to increase at historical rates? CS2710 Computer Organization4

5. Manufacturers have turned to multi-core architectures to bypass the Power Wall CS2710 Computer Organization5 Clock speed decrease, but overall performance increase

6. Lecture Objectives: 1)Explain the SPEC benchmarks. 2)Define Amdahl's law 3)Define MIPS

7. Amdahl’s Law (p51) The performance enhancement possible with a given improvement is limited by the amount that the improved feature is used CS2710 Computer Organization7

8. Amdahl’s Law Applied A Program spends 40 seconds performing network transfers and 60 seconds generating reports. – Suppose we could rewrite the report generator to make it more efficient. – What improvement in performance in the report generator would be necessary to increase the overall speed of the program by a factor of 2? – How about by a factor of 3? CS2710 Computer Organization8

9. A Performance Metric: MIPS Units: millions of instructions per second CS2710 Computer Organization9

10. Issues with MIPS metrics 1.Measures instruction execution rate, but doesn’t consider the complexity of the instructions performed 2.Average instruction complexity varies between programs executing on a single computer 3.Different microprocessors implement instructions of differing complexities MIPS may vary independently from performance We cannot compare computers with different instruction sets using MIPS! CS2710 Computer Organization10

11. Benchmarking: How do you decide which computer to buy? CS2710 Computer Organization11

12. SPEC Benchmark A set of 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) CS2710 Computer Organization12

13. Geometric vs. Arithmetic Mean Arithmetic mean: Geometric mean: CS2710 Computer Organization13

14. Which computer has better overall performance? CS2710 Computer Organization14 Computer AComputer BComputer C Program 111020 Program 2100010020

15. Which computer has better overall performance? CS2710 Computer Organization15 Computer AComputer BComputer C Program 111020 Program 2100010020 Arithmetic mean 500.55520 Geometric mean 31.622... 20 A is fastest via Arithmetic mean. A and B are tied via Geometric mean. Geometric mean is the appropriate mean when the ranges of the values being compared vary significantly.

16. Benchmarking often computes performance relative to a standard reference CS2710 Computer Organization16 Computer AComputer BComputer C Program 111020 Program 2100010020 Computer A (reference) Computer BComputer C Program 111020 Program 210.10.02 Scaling the results in this manner is called normalization. Note that no normalization was needed for Program 1 since the reference computer’s value was already 1. Let’s say A is the “reference” computer. We adjust all performance values by dividing each value by the reference computer’s value. In this example, we divide all results for Program 2 by the reference computer’s performance value of 1000, giving:

17. Arithmetic and Geometric means based on the normalized values: Computer AComputer BComputer C Program 111020 Program 210.10.02 Arithmetic mean 15.0510.01 Geometric mean 110.632... CS2710 Computer Organization17 Now C is fastest via Arithmetic mean! A and B are still tied via Geometric mean.

18. Now consider computer B to be the “reference” computer and normalize A and C w.r.t. B CS2710 Computer Organization18 Now A is fastest via Arithmetic mean! A and B are still tied via Geometric mean. The Geometric mean is consistent regardless of normalization! Computer A Computer B (reference) Computer C Program 10.112 Program 21010.2 Arithmetic mean 5.0511.1 Geometric mean 110.632

19. The SPECjvm2008 application – SPECjvm2008 is a benchmark suite for measuring the performance of a Java Runtime Environment (JRE), containing several real life applications and benchmarks focusing on core java functionality. – The SPECjvm2008 workload mimics a variety of common general purpose application computations. CS2710 Computer Organization19

20. CINT2006 integer performance benchmarks for the Opteron X4 2356 CS2710 Computer Organization20 NameDescriptionIC×10 9 CPITc (ns) Exec timeRef timeSPECratio perlInterpreted string processing2,1180.750.406379,77715.3 bzip2Block-sorting compression2,3890.850.408179,65011.8 gccGNU C Compiler1,0501.720.47248,05011.1 mcfCombinatorial optimization33610.000.401,3459,1206.8 goGo game (AI)1,6581.090.4072110,49014.6 hmmerSearch gene sequence2,7830.800.408909,33010.5 sjengChess game (AI)2,1760.960.483712,10014.5 libquantumQuantum computer simulation1,6231.610.401,04720,72019.8 h264avcVideo compression3,1020.800.4099322,13022.3 omnetppDiscrete event simulation5872.940.406906,2509.1 astarGames/path finding1,0821.790.407737,0209.1 xalancbmkXML parsing1,0582.700.401,1436,9006.0 Geometric mean11.7

21. SPEC and power: ssj_ops (server-side java operations/sec) Power consumption of server at different workload levels – Performance: ssj_ops/sec – Power: Watts (Joules/sec) CS2710 Computer Organization21

22. A Power benchmark: SPEC Power versus load SPECpower_ssj2008 for X4 CS2710 Computer Organization22 Target Load %Performance (ssj_ops/sec)Average Power (Watts) 100%231,867295 90%211,282286 80%185,803275 70%163,427265 60%140,160256 50%118,324246 40%920,35233 30%70,500222 20%47,126206 10%23,066180 0%0141 Overall sum1,283,5902,605 ∑ssj_ops/ ∑power493

23. Low power at low usage? No! Look back at X4 power benchmark – At 100% load: 295W – At 50% load: 246W (83%) – At 10% load: 180W (61%) Google data center – Mostly operates at 10% – 50% load – At 100% load less than 1% of the time Future research/development: Design processors to make power proportional to load CS2710 Computer Organization23