eddelbuettel/gcbd: '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.

Getting started

Package details

AuthorDirk Eddelbuettel
MaintainerDirk Eddelbuettel <edd@debian.org>
LicenseGPL (>= 2)
Version0.2.6
URL https://github.com/eddelbuettel/gcbd
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("eddelbuettel/gcbd")
eddelbuettel/gcbd documentation built on Feb. 16, 2024, 3:09 p.m.