Package: Rhpc 0.26.5

Ei-ji Nakama

Rhpc: Apply-Style Dispatch for High-Performance Computing

Provides apply-style functions using the Message Passing Interface ('MPI') to improve the High-Performance Computing ('HPC') environment in R. The package supports long vectors and efficient handling of large datasets for MPI-based parallel computations.

Authors:Ei-ji Nakama [aut, cre], Junji NAKANO [aut]

Rhpc_0.26.5.tar.gz
Rhpc_0.26.5.tar.gz(r-4.7-arm64)Rhpc_0.26.5.tar.gz(r-4.7-x86_64)Rhpc_0.26.5.tar.gz(r-4.6-arm64)Rhpc_0.26.5.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
Rhpc/json (API)

# Install 'Rhpc' in R:
install.packages('Rhpc', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/e-nakama/rhpc/issues

Uses libs:
  • openmpi– High performance message passing library

On CRAN:

Conda:

openmpi

3.30 score 5 scripts 791 downloads 20 exports 0 dependencies

Last updated from:043612cc59. Checks:5 OK, 5 FAIL. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK117
linux-devel-x86_64OK89
source / vignettesOK208
linux-release-arm64OK121
linux-release-x86_64OK96
windows-devel-arm64FAIL176
windows-devel-x86_64FAIL84
windows-release-arm64FAIL153
windows-release-x86_64FAIL79
wasm-releaseFAIL85

Exports:Rhpc_applyRhpc_enquoteRhpc_EvalQRhpc_ExportRhpc_finalizeRhpc_getHandleRhpc_initializeRhpc_lapplyRhpc_lapplyLBRhpc_numberOfWorkerRhpc_sapplyRhpc_sapplyLBRhpc_serializeRhpc_serialize_noreallocRhpc_serialize_onlysizeRhpc_setupRNGRhpc_splitListRhpc_unserializeRhpc_worker_callRhpc_worker_noback

Dependencies:

Introduction to Rhpc package
Rendered fromRhpc_intro.Rnwusingutils::Sweave

Last update: 2026-08-03
Started: 2026-07-21

Rhpcパッケージ入門 (Japanese)
Rendered fromRhpc_intro_ja.Rnwusingutils::Sweave

Last update: 2026-08-03
Started: 2026-07-21

Readme and manuals

Help Manual

Help pageTopics
Rhpc: MPI-based apply-style parallel computing for RRhpc-package Rhpc_gethandle Rhpc_mpi_finalize Rhpc_mpi_initialize Rhpc_mpi_lapply_LB Rhpc_mpi_lapply_seq Rhpc_mpi_worker_call Rhpc_number_of_worker
Parallel apply using MPIRhpc_apply
Quote arguments for remote evaluationRhpc_enquote
Evaluate an expression on worker processesRhpc_EvalQ
Export variables to worker processesRhpc_Export
Finalize MPI environmentRhpc_finalize
Get MPI communicator handleRhpc_getHandle
Initialize MPI environmentRhpc_initialize
Parallel lapply using MPIRhpc_lapply
Parallel lapply with load balancingRhpc_lapplyLB
Get number of worker processesRhpc_numberOfWorker
Parallel sapply using MPIRhpc_sapply
Parallel sapply with load balancingRhpc_sapplyLB
Serialize and unserialize R objectsRhpc_serialize Rhpc_serialize_norealloc Rhpc_serialize_onlysize Rhpc_unserialize
Setup random number generators for worker processesRhpc_setupRNG
Split a list into chunksRhpc_splitList
Call a function on worker processesRhpc_worker_call
Call a function on worker processes without collecting resultsRhpc_worker_noback