Version: 0.3-7
Date: 2024-11-11
Title: Programming with Big Data – Scalable Linear Algebra Packages
Depends: R (≥ 3.6.0), methods, pbdMPI (≥ 0.3-1)
LazyLoad: yes
Copyright: See 'pbdSLAP/inst/ScaLAPACK_LICENSE.txt' for the files in 'src/BLACS/', 'src/PBLAS/', 'src/REDIST/', 'src/ScaLAPACK/', and 'src/TOOLS/'.
Description: Utilizing scalable linear algebra packages mainly including 'BLACS', 'PBLAS', and 'ScaLAPACK' in double precision via 'pbdMPI' based on 'ScaLAPACK' version 2.0.2.
SystemRequirements: 'OpenMPI' (>= 1.5.4) on Solaris, Linux, Mac, and FreeBSD. 'MS-MPI' (Microsoft HPC Pack 2012 R2 MS-MPI Redistributable Package) on Windows.
License: Mozilla Public License 2.0
URL: https://pbdr.org/
BugReports: https://github.com/snoweye/pbdSLAP/issues
NeedsCompilation: yes
Maintainer: Wei-Chen Chen <wccsnow@gmail.com>
Packaged: 2024-11-12 01:56:22 UTC; snoweye
Author: Wei-Chen Chen [aut, cre], Drew Schmidt [aut], George Ostrouchov [aut], Pragneshkumar Patel [aut], Brian Ripley [ctb] (Solaris & Mac)
Repository: CRAN
Date/Publication: 2024-11-13 09:00:02 UTC

Programming with Big Data – Scalable Linear Algebra Packages

Description

pbdSLAP utilizes scalable linear algebra packages mainly including BLACS, PBLAS, and ScaLAPACK in double precision via pbdMPI based on ScaLAPACK version 2.0.2.

Details

This package requires pbdMPI and MPI system. The main purpose of pbdSLAP is to provide several scalable linear algebra packages containing double precision libraries for pbdDMAC or other useful packages.

Author(s)

Wei-Chen Chen wccsnow@gmail.com, Drew Schmidt, George Ostrouchov, and Pragneshkumar Patel.

References

Programming with Big Data in R Website: https://pbdr.org/

ScaLAPACK Website: https://netlib.org/scalapack/

ScaLAPACK Block Cyclic Data Distribution Website: https://icl.utk.edu/lapack-forum/viewtopic.php%3ff=5&t=4922.html

Examples

## Not run: 
### Under command mode, run the demo with 2 processors by
### (Use Rscript.exe for windows system)

mpiexec -np 2 Rscript -e "demo(gridinfo,'pbdSLAP',ask=F,echo=F)"

## End(Not run)

SLAP Grid

Description

These functions initializes a grid of pbdSLAP, assigns the information to a global object, and free the grid.

Usage

  slap.init.grid(nprow, npcol = 1, ictxt = 0)
  slap.exit.grid(ictxt)
  slap.finalize(quit.mpi = FALSE)

Arguments

nprow

number of row processors.

npcol

number of column processors.

ictxt

the grid id

quit.mpi

if finalize MPI.

Details

This function arranges all processors in a (nprow * npcol) grid and the grid will map the big data matrix.

Value

slap.init.grid assigns a global object .__grid_info_0 for ictxt = 0 containing the grid information. slap.exit.grid free the grid. slap.finalize free all memory.

Author(s)

Wei-Chen Chen wccsnow@gmail.com, Drew Schmidt, George Ostrouchov, and Pragneshkumar Patel.

References

Programming with Big Data in R Website: https://pbdr.org/

ScaLAPACK Website: https://netlib.org/scalapack/

ScaLAPACK Block Cyclic Data Distribution Website: https://icl.utk.edu/lapack-forum/viewtopic.php%3ff=5&t=4922.html

Examples

## Not run: 
### Under command mode, run the demo with 2 processors by
### (Use Rscript.exe for windows system)

mpiexec -np 2 Rscript -e "demo(gridinfo,'pbdSLAP',ask=F,echo=F)"

## End(Not run)

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