Understanding Energy Behaviors of Thread Management Constructs

Transcript

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   Understanding Energy Behaviors of Thread Management Constructs Gustavo Pinto1 Fernando

   Castor1 David Liu2 {ghlp, castor}@cin.ufpe.br1 davidL@binghamton.edu2
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   2 • First, the proliferation of multicore CPUs • Second,

   the prevalence of multi-threaded programs Motivation
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   3 • First, more cores more power consumed • Second,

   little is known about energy behaviors of multi-threaded program on the application and programming language level The Problem
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   4 1. programming abstractions of thread management on energy efficiency

   2. programmer choices of thread management on energy efficiency This Talk for Java multi-threaded programs
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   5 • Explicit threading (the Thread-style): Using the java.lang.Thread class

   • Thread pooling (the Executor-style): Using the java.util.concurrent.Executor framework • Working Stealing (the ForkJoin-style): Using the java.util.concurrent.ForkJoin framework Thread management constructs
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   6 • Embarrassingly parallel: spectralnorm, sunflow, n-queens • Leaning parallel:

   xalan, knucleotide, tomcat • Leaning serial: mandelbrot, largestImage • Embarrassingly serial: h2 Benchmarks
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   7 • Embarrassingly parallel: spectralnorm, sunflow, n-queens • Leaning parallel:

   xalan, knucleotide, tomcat • Leaning serial: mandelbrot, largestImage • Embarrassingly serial: h2 Benchmarks Micro-benchmarks DaCapo benchmarks
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   8 Experimental Environment A 2×16-core AMD CPUs, running Debian Linux,

   64GB of memory, JDK version 1.7.0 11, build 21, “ondemand” governor
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   9 Experimental Environment A 2×16-core AMD CPUs, running Debian Linux,

   64GB of memory, JDK version 1.7.0 11, build 21, “ondemand” governor
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    10 Experimental Environment A 2×16-core AMD CPUs, running Debian Linux,

    64GB of memory, JDK version 1.7.0 11, build 21.
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    11 Experimental Environment A 2×16-core AMD CPUs, running Debian Linux,

    64GB of DDR3 1600 memory, and JDK version 1.7.0 11, build 21.
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    Energy Consumption When Varying the Number of Threads 12

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    13 The Λ Curve

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    14 The Λ Curve

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    15 The Λ Curve

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    16 More cores idle CPU frequency at a lower level

    The Λ Curve
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    17 More cores idle CPU frequency at a lower level

    More threads used, program completes sooner The greater the ratio between speedup and power, the steeper the \ The Λ Curve
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    Which programming style should I use? 18 ? ?

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    Overpopulating Cores with Threads 19

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    Overpopulating Cores with Threads 20

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    Faster ≠ Greener 21

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    Copying vs Sharing 22

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    Copying vs Sharing 23 Copying

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    Copying vs Sharing 24 Copying Sharing

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    Copying vs Sharing 25 Copying Sharing ±15% of energy savings!

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    26 Copy-Fork

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    27 After Before Copy-Fork

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    28 After Before Copy-Fork Copy/Fork/Copy/Fork/…

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    29 After Before Copy-Fork Copy/Fork/Copy/Fork/…

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    30 After Before Copy-Fork Copy/Fork/Copy/Fork/… Copy/../Copy/Fork/…/Fork

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    31 After Before Copy-Fork ±10% of energy savings! Copy/Fork/Copy/Fork/… Copy/../Copy/Fork/…/Fork

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    Data Size 32

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    Data Size 33 For most of the cases, energy consumption

    is linear to data size!
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    Understanding Energy Behaviors of Thread Management Constructs Gustavo Pinto1 Fernando

    Castor1 David Liu2 {ghlp, castor}@cin.ufpe.br1 davidL@binghamton.edu2