An efficient interface to MPI by utilizing S4
classes and methods with a focus on Single Program/Multiple Data ('SPMD')
parallel programming style, which is intended for batch parallel
execution.

OpenMPI (>= 1.5.4) on Solaris, Linux, Mac, and
FreeBSD. MS-MPI (Microsoft MPI v7.1 (SDK) and Microsoft HPC
Pack 2012 R2 MS-MPI Redistributable Package) on Windows.

An efficient interface to MPI by utilizing S4
classes and methods with a focus on Single Program/Multiple Data
('SPMD')
parallel programming style, which is intended for batch parallel
execution.

c(person("Wei-Chen", "Chen", role = c("aut", "cre"), email =
"wccsnow@gmail.com"),
person("George", "Ostrouchov", role = "aut"),
person("Drew", "Schmidt", role = "aut"),
person("Pragneshkumar", "Patel", role = "aut"),
person("Hao", "Yu", role = "aut"),
person("Christian", "Heckendorf", role = "ctb", comment = "FreeBSD"),
person("Brian", "Ripley", role = "ctb", comment = "Windows HPC Pack
2012"),
person("R Core team", role = "ctb", comment = "some functions are
modified from the base packages"),
person("Sebastien", "Lamy de la Chapelle", role="aut", comment = "fix
check type for send/recv long vectors"))
Wei-Chen Chen [aut, cre],
George Ostrouchov [aut],
Drew Schmidt [aut],
Pragneshkumar Patel [aut],
Hao Yu [aut],
Christian Heckendorf [ctb] (FreeBSD),
Brian Ripley [ctb] (Windows HPC Pack 2012),
R Core team [ctb] (some functions are modified from the base packages),
Sebastien Lamy de la Chapelle [aut] (fix check type for send/recv long
vectors)

Programming with Big Data -- Interface to Parallel Unidata
NetCDF4 Format Data Files
c(person("Pragneshkumar", "Patel", role = c("aut", "cre"),
email = "pragnesh@utk.edu"), person("George", "Ostrouchov",
role = "aut"), person("Wei-Chen", "Chen", role = "aut"),
person("Drew", "Schmidt", role = "aut"), person("David",
"Pierce", role = "aut"))
R (>= 2.13.0), methods, rlecuyer, pbdMPI (>= 0.1-4)
This package adds collective parallel read and write
capability to the R package ncdf4 version 1.8. Typical use is
as a parallel NetCDF4 file reader in SPMD style programming.
Each R process reads and writes its own data in a synchronized
collective mode, resulting in faster parallel performance.
Performance improvement is conditional on a parallel file
system.
OpenMPI (>= 1.5.4) on Solaris, Linux and Mac.
Parallel HDF5 and NetCDF4 (4.1 or later) libraries.
Pragneshkumar Patel [aut, cre], George Ostrouchov [aut],
Wei-Chen Chen [aut], Drew Schmidt [aut], David Pierce [aut]