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

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

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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

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

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

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

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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

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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

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

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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

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

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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

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

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

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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.

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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:

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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.

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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

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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

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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

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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

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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

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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

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Copyright © 1998 Wanda Kunkle Computer Organization 1 Chapter 2.5 Comparing and Summarizing Performance.

Copyright © 1998 Wanda Kunkle Computer Organization 1 Chapter 2.5 Comparing and Summarizing Performance.

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