'GPU'/CPU Benchmarking in Debian-Based Systems

'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 current version supports - 'Reference BLAS' ('refblas') which are un-accelerated 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 multi-threaded - 'Intel MKL' which is 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.


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.

News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("gcbd")

0.2.6 by Dirk Eddelbuettel, a year ago


Browse source code at https://github.com/cran/gcbd


Authors: Dirk Eddelbuettel


Documentation:   PDF Manual  


Task views: High-Performance and Parallel Computing with R


GPL (>= 2) license


Imports Matrix, DBI, RSQLite, plyr, reshape, lattice

Suggests gputools

System requirements: Debian or Ubuntu system with access to Goto Blas, Intel MKL, Atlas development build as well as a Nvidia GPU with CUDA support


See at CRAN