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pbdDMAT

pbdDMAT is an R package for distributed matrix algebra and statistics computations over MPI.

With few exceptions (ff, bigalgebra, etc.), R does computations in memory. If the memory of a matrix is too large for a single node, then distributing the ownership of the matrix across multiple nodes is an effective strategy in working with such large data.

The pbdDMAT package contains numerous routines to help with the distribution and management of data, as well as functions for summarizing, inspecting, and analyzing distributed matrices.

Often the syntax is identical to serial R, only instead of calling cov(x) on a matrix x, you would call it on a distributed matrix x. This is possible by extensive use of R's S3 and S4 methods.

Much of the numerical linear algebra is powered by the ScaLAPACK library, which is the distributed analogue of LAPACK, used extensively by R.

Installation

pbdDMAT requires

  • A system installation of MPI
  • R version 3.0.0 or higher
  • The pbdMPI and pbdBASE packages, as well as their dependencies.

Assuming you meet the system dependencies, you can install the stable version from CRAN using the usual install.packages():

install.package("pbdDMAT")

The development version is maintained on GitHub:

remotes::install_github("RBigData/pbdDMAT")

See the vignette for installation troubleshooting.

Usage

# load the package
library(pbdDMAT)

# initialize the specialized MPI communicators
init.grid()

# create a 100x100 distributed matrix object
dx <- ddmatrix(1:100, 10)

# print
dx
print(dx, all=TRUE)


# shut down the communicators and exit
finalize()

Save this program as pbd_example.r and run it via:

mpirun -np 2 Rscript pbd_example.r

Numerous other examples can be found in both the pbdDMAT vignette, as well as the pbdDEMO package and its corresponding vignette.

Authors

pbdDMAT is authored and maintained by the pbdR core team:

  • Drew Schmidt
  • Wei-Chen Chen
  • George Ostrouchov
  • Pragneshkumar Patel

With additional contributions from:

  • Lamy de la Chapelle Sebastien
  • The R Core team (some wrapper code taken from the base and stats packages)
  • ZhaoKang Wang (fixes/improvements to apply())
  • Michael Lawrence (fix for as.vector())

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Version

Install

install.packages('pbdDMAT')

Monthly Downloads

114

Version

0.5-1

License

GPL (>= 2)

Maintainer

Last Published

March 17th, 2019

Functions in pbdDMAT (0.5-1)

binds

Row and Column binds for Distributed Matrices
ddmatrix-lu

LU Factorization
ddmatrix-chol

Cholesky Factorization
ddmatrix-prcomp

Principal Components Analysis
ddmatrix-eigen

eigen
isdot

Type Checks, Including NA, NaN, etc.
getLocal

getLocal
headsortails

Head and Tail of a Distributed Matrix
qr

QR Decomposition Methods
redistribute

Distribute/Redistribute matrices across the process grid
sd

Covariance and Correlation
sparsity

Sparsity of Matrix Objects
as.ddmatrix

Non-Distributed object to Distributed Object Converters
extract

Extract or Replace Parts of a Distributed Matrix
as.matrix

Distributed object to Matrix Converters
ddmatrix-print

Printing a Distributed Matrix
ddmatrix-summary

Distributed Matrix Summary
ddmatrix-apply

Apply Family of Functions
Accessors

Accessor Functions for Distributed Matrix Slots
expm

Matrix Exponentiation
sweep

Sweep
ddmatrix-scale

Scale
companion

Generate Companion Matrices
ddmatrix-class

Class ddmatrix
lm.fit

Fitter for Linear Models
pbdDMAT Control

Some default parameters for pbdDMAT.
transpose

Distributed Matrix Transpose
arithmetic

Arithmetic Operators
diag-constructors

Distributed Matrix Diagonals
covariance

Covariance and Correlation
eigen2

eigen2
as.rowcyclic

Distribute/Redistribute matrices across the process grid
as.vector

Distributed object to Vector Converters
condnums

Compute or estimate the Condition Number of a Distributed Matrix
ddmatrix-solve

Solve
ddmatrix-constructors

Distributed Matrix Creation
insert

Directly Insert Into Distributed Matrix Submatrix Slot
math

Miscellaneous Mathematical Functions
matmult

Matrix Multiplication
reductions

Arithmetic Reductions: Sums, Means, and Prods
ddmatrix-sumstats

Basic Summary Statistics
pbdDMAT-package

Distributed Matrix Methods
na

Handle Missing Values in Distributed Matrices
rounding

Rounding of Numbers
ddmatrix-svd

Singular Value Decomposition
isSymmetric

isSymmetric
Comparators

Logical Comparisons
chol2inv

Inverse from Choleski (or QR) Decomposition
Hilbert

Generate Hilbert Matrices
ddmatrix-norm

Norm