https://github.com/eddelbuettel/gcbd

R package for GPU/CPU benchmarking on Debian-based systems
https://github.com/eddelbuettel/gcbd

cran gpu r r-package

Last synced: 8 months ago
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R package for GPU/CPU benchmarking on Debian-based systems

• Host: GitHub
• URL: https://github.com/eddelbuettel/gcbd
• Owner: eddelbuettel
• Created: 2013-12-12T00:30:33.000Z (over 12 years ago)
• Default Branch: master
• Last Pushed: 2024-10-29T23:39:24.000Z (over 1 year ago)
• Last Synced: 2025-02-01T20:15:56.891Z (over 1 year ago)
• Topics: cran, gpu, r, r-package
• Language: R
• Homepage:
• Size: 1.08 MB
• Stars: 8
• Watchers: 3
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Changelog: ChangeLog

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README

          
# gcbd

[![CI](https://github.com/eddelbuettel/gcbd/workflows/ci/badge.svg)](https://github.com/eddelbuettel/gcbd/actions?query=workflow%3Aci)

## 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.