Benchmarking functions for GPU/CPU Benchmarking

Description

Benchmarking functions for GPU/CPU Benchmarking

Usage

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  getMatrix(N)
  matmultBenchmark(N, n, trim=0.1)
  matmultBenchmarkgputools(N, n, trim=0.1)
  qrBenchmark(N, n, trim=0.1)
  qrBenchmarkgputools(N, n, trim=0.1)
  svdBenchmark(N, n, trim=0.1)

  luBenchmark(N, n, trim=0.1)
  luBenchmarkgputools(N, n, trim=0.1)

Arguments

N

dimension of square matrix

n

number of replications of benchmarked test

trim

percentage to be trimmed in mean estimation

Details

getMatrix provides a square matrix of the given dimension.

matmultBenchmark times the cost of multiplying a matrix of the given size with itself, repeated as specified and returns the trimmed mean of the elapsed times. matmultBenchmarkgputools does the same using the gputools and packages.

qrBenchmark times the cost of a QR decomposition of a matrix of the given size, repeated as specified and returns the trimmed mean of the elapsed times. qrBenchmarkgputools does the same using the gputools packages.

svdBenchmark times the cost of a Singular Value Decomposition (SVD) of a matrix of the given size, repeated as specified and returns the trimmed mean of the elapsed times.

luBenchmark times the cost of a LU Decomposition of a matrix of the given size, repeated as specified and returns the trimmed mean of the elapsed times. luBenchmarkgputools does the same using the gputools package.