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gcbd
View on CRAN: Click
here
Download and install gcbd package within the R console
Install from CRAN:
install.packages("gcbd")
Install from Github:
library("remotes")
install_github("cran/gcbd")
Install by package version:
library("remotes")
install_version("gcbd", "0.2.6")
Attach the package and use:
library("gcbd")
Maintained by
Dirk Eddelbuettel
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2010-09-15
Latest Update: 2016-09-28
Description:
'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.
How to cite:
Dirk Eddelbuettel (2010). gcbd: 'GPU'/CPU Benchmarking in Debian-Based Systems. R package version 0.2.6, https://cran.r-project.org/web/packages/gcbd
Previous versions and publish date:
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Functions, R codes and Examples using
the gcbd R package
Some associated functions: analysis . benchmark . figures . utilities .
Some associated R codes: analysis.R . benchmark.R . figures.R . utilities.R . zzz.R . Full gcbd package functions and examples
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