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.


pbdDMAT requires

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


The development version is maintained on GitHub, and can easily be installed by any of the packages that offer installations from GitHub:

### Pick your preference

See the vignette for installation troubleshooting.


# load the package

# initialize the specialized MPI communicators

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

# print
print(dx, all=TRUE)

# shut down the communicators and exit

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.


pbdDMAT is authored and maintained by the pbdR core team:

With additional contributions from:

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pbdDMAT documentation built on May 29, 2017, 1:23 p.m.