This package is considered a duplicate. The official version of this package is found at:https://jrmccombs.r-universe.dev/RHPCBenchmark

Package: RHPCBenchmark 0.1.0

James McCombs

RHPCBenchmark: Benchmarks for High-Performance Computing Environments

Microbenchmarks for determining the run time performance of aspects of the R programming environment and packages relevant to high-performance computation. The benchmarks are divided into three categories: dense matrix linear algebra kernels, sparse matrix linear algebra kernels, and machine learning functionality.

Authors:James McCombs [aut, cre]

RHPCBenchmark_0.1.0.tar.gz
RHPCBenchmark_0.1.0.zip(r-4.7-any)RHPCBenchmark_0.1.0.zip(r-4.6-any)RHPCBenchmark_0.1.0.zip(r-4.5-any)
RHPCBenchmark_0.1.0.tgz(r-4.6-any)RHPCBenchmark_0.1.0.tgz(r-4.5-any)
RHPCBenchmark_0.1.0.tar.gz(r-4.7-any)RHPCBenchmark_0.1.0.tar.gz(r-4.6-any)
RHPCBenchmark_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
RHPCBenchmark/json (API)

# Install 'RHPCBenchmark' in R:

install.packages('RHPCBenchmark', repos = c('https://cranhaven.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/cranhaven/cranhaven.r-universe.dev/issues

On CRAN:

archived packages r-universe

3.72 score 5 stars 21 scripts 239 downloads 48 exports 4 dependencies

Last updated from:a8fc13ef51 (on package/RHPCBenchmark). Checks:7 NOTE, 2 OK. Indexed: no.

Target	Result	Time
linux-devel	NOTE	106
source / vignettes	OK	182
linux-release	NOTE	98
macos-release	NOTE	78
macos-oldrel	NOTE	96
windows-devel	NOTE	81
windows-release	NOTE	61
windows-oldrel	NOTE	68
wasm-release	OK	79

Exports:CholeskyAllocator CholeskyMicrobenchmark ClaraClusteringMicrobenchmark ClusteringAllocator CrossprodAllocator CrossprodMicrobenchmark DeformtransAllocator DeformtransMicrobenchmark DeterminantAllocator DeterminantMicrobenchmark EigenAllocator EigenMicrobenchmark GetClusteringDefaultMicrobenchmarks GetClusteringExampleMicrobenchmarks GetDenseMatrixDefaultMicrobenchmarks GetDenseMatrixExampleMicrobenchmarks GetSparseCholeskyDefaultMicrobenchmarks GetSparseCholeskyExampleMicrobenchmarks GetSparseLuDefaultMicrobenchmarks GetSparseMatrixVectorDefaultMicrobenchmarks GetSparseMatrixVectorExampleMicrobenchmarks GetSparseQrDefaultMicrobenchmarks LsfitAllocator LsfitMicrobenchmark MatmatAllocator MatmatMicrobenchmark MatvecAllocator MatvecMicrobenchmark PamClusteringMicrobenchmark QrAllocator QrMicrobenchmark RunDenseMatrixBenchmark RunMachineLearningBenchmark RunSparseMatrixBenchmark SolveAllocator SolveMicrobenchmark SparseCholeskyAllocator SparseCholeskyMicrobenchmark SparseLuAllocator SparseLuMicrobenchmark SparseMatrixVectorAllocator SparseMatrixVectorMicrobenchmark SparseQrAllocator SparseQrMicrobenchmark SvdAllocator SvdMicrobenchmark TransposeAllocator TransposeMicrobenchmark

Dependencies:cluster lattice Matrix mvtnorm

R HPC Benchmark

Rendered fromvignette.Rmdusingknitr::rmarkdown

Last update: 2026-10-12
Started: 2026-10-12

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Allocates and initializes input to the Cholesky factorization dense matrix kernel microbenchmarks	CholeskyAllocator
Conducts a single performance trial with the Cholesky factorization dense matrix kernel	CholeskyMicrobenchmark
Conducts a single performance trial with the cluster::clara function	ClaraClusteringMicrobenchmark
Allocates and initializes input to the clustering for machine learning microbenchmarks	ClusteringAllocator
This class specifies a clustering for machine learning microbenchmark.	ClusteringMicrobenchmark
Computes the average of a vector of performance trial times	ComputeAverageTime
Computes the standard deviation of a vector of performance trial times	ComputeStandardDeviation
Allocates and populates input to the matrix cross product dense matrix kernel microbenchmarks	CrossprodAllocator
Conducts a single performance trial with the matrix cross product dense matrix kernel	CrossprodMicrobenchmark
Allocates and populates input to the matrix deformation and transpose dense matrix kernel microbenchmarks	DeformtransAllocator
Conducts a single performance trial with the matrix deformation and transpose dense matrix kernel	DeformtransMicrobenchmark
This class specifies a dense matrix microbenchmark.	DenseMatrixMicrobenchmark
Allocates and populates input to the matrix determinant dense matrix kernel microbenchmarks	DeterminantAllocator
Conducts a single performance trial with the matrix determinant dense matrix kernel	DeterminantMicrobenchmark
Allocates and populates input to the matrix eigendecomposition kernel microbenchmarks	EigenAllocator
Conducts a single performance trial with the matrix eigendecomposition dense matrix kernel	EigenMicrobenchmark
Generates clusters from multivariate normal distributions	GenerateClusterData
Initializes the list of default clustering microbenchmarks	GetClusteringDefaultMicrobenchmarks
Initializes the list of example clustering microbenchmarks	GetClusteringExampleMicrobenchmarks
Retrieves the value of an environment variable referenced by another environment variable	GetConfigurableEnvParameter
Initializes the list of default dense matrix microbenchmarks	GetDenseMatrixDefaultMicrobenchmarks
Initializes the list of example dense matrix microbenchmarks	GetDenseMatrixExampleMicrobenchmarks
Retrieves the number of threads from the environment	GetNumberOfThreads
Initializes the list of default sparse Cholesky factorization microbenchmarks	GetSparseCholeskyDefaultMicrobenchmarks
Initializes the list of example sparse Cholesky factorization microbenchmarks	GetSparseCholeskyExampleMicrobenchmarks
Initializes the list of default sparse LU factorization microbenchmarks	GetSparseLuDefaultMicrobenchmarks
Initializes the list of default sparse matrix-vector microbenchmarks	GetSparseMatrixVectorDefaultMicrobenchmarks
Initializes the list of example sparse matrix-vector microbenchmarks	GetSparseMatrixVectorExampleMicrobenchmarks
Initializes the list of default sparse QR factorization microbenchmarks	GetSparseQrDefaultMicrobenchmarks
Allocates and populates input to the matrix least squares fit dense matrix kernel microbenchmarks	LsfitAllocator
Conducts a single performance trial with the matrix least squares fit dense matrix kernel	LsfitMicrobenchmark
Allocates and populates input to the matrix-matrix multiplication dense matrix kernel microbenchmarks	MatmatAllocator
Conducts a single performance trial with the matrix-matrix multiplication dense matrix kernel	MatmatMicrobenchmark
Allocates and populates input to the matrix-vector multiplication dense matrix kernel microbenchmarks	MatvecAllocator
Conducts a single performance trial with the matrix-vector multiplication dense matrix kernel	MatvecMicrobenchmark
Performs microbenchmarking of a clustering for machine learning kernel	MicrobenchmarkClusteringKernel
Performs microbenchmarking of a dense matrix linear algebra kernel	MicrobenchmarkDenseMatrixKernel
Performs microbenchmarking of a sparse matrix linear algebra kernel	MicrobenchmarkSparseMatrixKernel
Conducts a single performance trial with the cluster::pam function	PamClusteringMicrobenchmark
Performs microbenchmarking of machine learning functions specified by an input list	PerformClusteringMicrobenchmarking
Performs microbenchmarking of sparse matrix kernels specified by an input list	PerformSparseMatrixKernelMicrobenchmarking
Prints results of a clustering for machine learning microbenchmark	PrintClusteringMicrobenchmarkResults
Prints results of a dense matrix microbenchmark	PrintDenseMatrixMicrobenchmarkResults
Prints results of a sparse matrix microbenchmark	PrintSparseMatrixMicrobenchmarkResults
Allocates and populates input to the QR factorization dense matrix kernel microbenchmarks	QrAllocator
Conducts a single performance trial with the QR factorization dense matrix kernel	QrMicrobenchmark
RHPCBenchmark: A package for performance testing intrinsic R functionality and established packages relevant to high-performance computing	RHPCBenchmark-package RHPCBenchmark
Runs all of the dense matrix microbenchmarks	RunDenseMatrixBenchmark
Runs all of the machine learning microbenchmarks	RunMachineLearningBenchmark
Runs all of the sparse matrix microbenchmarks	RunSparseMatrixBenchmark
Allocates and populates input to the dense matrix kernel microbenchmark for computing the solution to a system of linear equations with multiple right-hand sides	SolveAllocator
Conducts a single performance trial with the dense matrix kernel for computing the solution to a system of linear equations with multiple right-hand sides	SolveMicrobenchmark
Allocates and initializes input to the Cholesky factorization sparse matrix kernel microbenchmarks	SparseCholeskyAllocator
Conducts a single performance trial with the Cholesky factorization sparse matrix kernel	SparseCholeskyMicrobenchmark
Allocates and initializes input to the LU factorization sparse matrix kernel microbenchmarks	SparseLuAllocator
Conducts a single performance trial with the LU factorization sparse matrix kernel	SparseLuMicrobenchmark
This class specifies a sparse matrix microbenchmark.	SparseMatrixMicrobenchmark
Allocates and initializes input to the matrix-vector multiplication sparse matrix kernel microbenchmarks	SparseMatrixVectorAllocator
Conducts a single performance trial with the matrix-vector multiplication sparse matrix kernel	SparseMatrixVectorMicrobenchmark
Allocates and initializes input to the QR factorization sparse matrix kernel microbenchmarks	SparseQrAllocator
Conducts a single performance trial with the QR factorization sparse matrix kernel	SparseQrMicrobenchmark
Allocates and populates input to the singular value decomposition (SVD) dense matrix kernel microbenchmarks	SvdAllocator
Conducts a single performance trial with the singular value decomposition (SVD) dense matrix kernel	SvdMicrobenchmark
Allocates and populates input to the matrix transpose dense matrix kernel microbenchmarks	TransposeAllocator
Conducts a single performance trial with the matrix transpose dense matrix kernel	TransposeMicrobenchmark
Appends performance test results of a clustering microbenchmark to a file in CSV format	WriteClusteringPerformanceResultsCsv
Appends dense matrix performance test results to a file in CSV format	WriteDenseMatrixPerformanceResultsCsv
Appends sparse matrix performance test results to a file in CSV format	WriteSparseMatrixPerformanceResultsCsv