pbdDMAT: Programming with Big Data – Distributed Matrix Methods

pbdDMAT contains high level S3 and S4 methods for creating, modifying, and performing computations with dense, distributed matrices. This includes a new class, 'ddmatrix', for storing all of the distributed data details. Computation is handled mostly by routines from the pbdBASE package.

Version: 0.2-3
Depends: R (≥ 2.14.0), methods, rlecuyer, pbdMPI (≥ 0.2-1), pbdSLAP (≥ 0.1-6), pbdBASE (≥ 0.2-3)
Published: 2013-12-16
Author: Drew Schmidt [aut, cre], Wei-Chen Chen [aut], George Ostrouchov [aut], Pragneshkumar Patel [aut], R Core team [ctb] (some wrappers taken from the base and stats packages)
Maintainer: Drew Schmidt <schmidt at math.utk.edu>
BugReports: http://group.r-pbd.org/
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://r-pbd.org/
NeedsCompilation: No
SystemRequirements: OpenMPI (>= 1.5.4) on Solaris, Linux and Mac, MPICH2 (>= 1.4.1p1) on Windows
Citation: pbdDMAT citation info
Materials: README ChangeLogINSTALL
In views: HighPerformanceComputing
CRAN checks: pbdDMAT results

Downloads:

Reference manual: pbdDMAT.pdf
Vignettes: pbdDMAT-guide
Package source: pbdDMAT_0.2-3.tar.gz
MacOS X binary: pbdDMAT_0.2-3.tgz
Windows binary: not available, see ReadMe.
Old sources: pbdDMAT archive

Reverse dependencies:

Reverse depends: pbdDEMO
Reverse enhances: pmclust