With few exceptions (ff, bigalgebra, etc.), R does computations in memory. When data becomes too large to handle in the memory of a single node, or when more processors than those offered in commodity hardware (~16) are needed for a job, a typical strategy is to add more nodes. MPI, or the “Message Passing Interface”, is the standard for managing multi-node communication. pbdMPI is a package that greatly simplifies the use of MPI from R.

In pbdMPI, we make extensive use of R’s S4 system to simplify the interface significantly. Instead of needing to specify the type (e.g., integer or double) of the data via function name (as in C implementations) or in an argument (as in Rmpi), you need only call the generic function on your data and we will always “do the right thing”.

In pbdMPI, we write programs in the “Single Program/Multiple Data” or SPMD style. Contrary to the way much of the R world is aquainted with parallelism, there is no “master” or “manager”. Each process (MPI rank) gets runs the same copy of the program as every other process, but operates on its own data. This is arguably one of the simplest extensions of serial to massively parallel programming, and has been the standard way of doing things in the HPC community for over 20 years.


If you are comfortable with MPI concepts, you should find pbdMPI very agreeable and simple to use. Below is a basic “hello world” program:

# load the package
suppressMessages(library(pbdMPI, quietly = TRUE))

# initialize the MPI communicators

# Hello world
message <- paste("Hello from rank", comm.rank(), "of", comm.size())
comm.print(message, all.rank=TRUE, quiet=TRUE)

# shut down the communicators and exit

Save this as, say, mpi_hello_world.r and run it via:

mpirun -np 4 Rscript mpi_hello_world.r

The function comm.print() is a “sugar” function custom to pbdMPI that makes it simple to print in a distributed environment. The argument all.rank=TRUE specifies that all MPI ranks should print, and the quiet=TRUE argument tells each rank not to “announce” itself when it does its printing.

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


pbdMPI requires * R version 3.0.0 or higher * A system installation of MPI: - SUN HPC 8.2.1 (OpenMPI) for Solaris. - OpenMPI for Linux. - OpenMPI for Mac OS X. - MS-MPI for Windows.

The package can be installed from the CRAN via the usual install.packages("pbdMPI"), or via the devtools package:


For additional installation information, see: - see “INSTALL” for Solaris, Linux and Mac OS. - see “INSTALL.win.*" for Windows.

More information about pbdMPI, including installation troubleshooting, can be found in:

  1. pbdMPI vignette at ‘pbdMPI/inst/doc/pbdMPI-guide.pdf’.
  2. ‘http://r-pbd.org/’.


pbdMPI is authored and maintained by the pbdR core team: * Wei-Chen Chen * George Ostrouchov * Drew Schmidt * Pragneshkumar Patel

With additional contributions from: * Hao Yu * Christian Heckendorf * Brian Ripley (Windows HPC Pack 2012) * The R Core team (some functions are modified from the base packages)