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 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.

Version: 0.2.5
Depends: R (≥ 2.11.1), RSQLite, plyr, reshape, lattice
Suggests: gputools, Matrix
OS_type: unix
Published: 2013-12-12
Author: Dirk Eddelbuettel
Maintainer: Dirk Eddelbuettel <edd at debian.org>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
SystemRequirements: Debian or Ubuntu system with access to Goto Blas, Intel MKL, Atlas development build as well as a Nvidia GPU with CUDA support
Materials: README ChangeLog
In views: HighPerformanceComputing
CRAN checks: gcbd results

Downloads:

Reference manual: gcbd.pdf
Vignettes: BLAS and GPU Benchmarking for Use with R
Package source: gcbd_0.2.5.tar.gz
MacOS X binary: gcbd_0.2.5.tgz
Windows binary: not available, see ReadMe.
Old sources: gcbd archive