Learn R Programming

gcbd

GPU/CPU Benchmarking on Debian-package based systems

This package benchmarks performance of a few standard linear algebra operations (such as a matrix product and QR, SVD and LU decompositions) across a number of different BLAS libraries as well as a GPU implementation.

To do so, it takes advantage of the ability to 'plug and play' different BLAS implementations easily on a Debian and/or Ubuntu system. The initial version supported

  • reference blas (refblas) which are unaccelerated as a baseline
  • Atlas which are tuned but typically configure single-threaded
  • Atlas39 which are tuned and configured for multi-threaded mode
  • Goto Blas which are accelerated and multithreaded
  • Intel MKL which are a commercial accelerated and multithreaded version.

As for GPU computing, we use the CRAN package

  • gputools

For Goto Blas, the gotoblas2-helper script from the ISM in Tokyo can be used. For Intel MKL we use the Revolution R packages from Ubuntu 9.10.

Copy Link

Version

Install

install.packages('gcbd')

Monthly Downloads

158

Version

0.2.6

License

GPL (>= 2)

Last Published

September 28th, 2016

Functions in gcbd (0.2.6)

analysis

Analysis functions for GPU/CPU Benchmarking
figures

Figures from the corresponding vignette
benchmark

Benchmarking functions for GPU/CPU Benchmarking
utilities

Utility functions for GPU/CPU Benchmarking