Measuring the performance improvements as you parallelize and - - PowerPoint PPT Presentation

Measuring the performance improvements as you parallelize and optimize your software

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• O2 -march=native -mtune=native -ftree-vectorize

0.25 s

• O2 -march=native -mtune=native -ftree-vectorize

0.27 s managing race conditions with... OpenMP pragma atomic

• O2 -march=native -mtune=native -ftree-vectorize -fopenmp

0.359 s 0.7x

• O2 -march=native -mtune=native -ftree-vectorize -fopenmp

0.3470 s 0.78x OpenMP privatization

• f arrays
• O2 -march=native -mtune=native -ftree-vectorize -fopenmp

0.1172 s 2.13x

• O2 -march=native -mtune=native -ftree-vectorize -fopenmp

0.1177 s 2.29x

Multiplication of Transposed Sparse Matrix by Vector

• Evaluate the performance of your serial, parallel and optimized code

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• Tuning and optimization:

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• Avoiding ‘too much parallel’

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Ideal Real Threads Processes Cores Speedup

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• Serial and parallel performance
• Take regular parallel performance measurements as you progress

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• Understand your performance limits

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Use Speedup and Efficiency measures

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• Measure the relative performance between serial and parallel code.
• Improvement in speed of execution of a task executed on the same architecture but

with different resources Speedup, S, for problem size N on P processes/threads/cores

• Tips:

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T(N,1) T(N,P) S(N, P)

=

• Measure the efficiency of the parallel code.
• 100% efficiency = using double the resources, but taking half the runtime (i.e. the

same resources are used in total) Parallel efficiency, E, for problem size N on P processes/threads/cores

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S(N,P) P T(N,1) (P*T(N,P)) E(N, P) = =

• We can never parallelize every single part of code (e.g. initialising and distributing the data).
• A fraction of the runtime, α, is completely serial, limiting the parallel runtime even with 100%

efficiency of the parallel fraction on P processors/threads/cores.

• Limited by the serial fraction:

○ α ○ α ■ α

For runtime T, using problem size N for P processes

Known as ‘Amdahl’s Law’

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(1-α)T(N,1) P T= α T(N,1) +

Gene Amdahl, 1967

(1-α)=90% α=10%

α=50% α=25% α=10% α =5%

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α =sequential

portion 1x 2x 3.7x 1 2 4 8 Processors Parallel Serial 1x 1.33x 1.6x 1.8x 1 2 4 8 Processors Parallel Serial

α=50% (1-α)=50%

Source: Wikipedia

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• Use the spreadsheet assigned to your team to record timings

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• Use this regularly, particularly once you start trying multiple parallelization

methods and tuning your implementations.

• Try and gain an understanding of your serial fraction, α

○ ○ α

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