Package: RHPCBenchmark 0.1.0

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-4.5)RHPCBenchmark_0.1.0.zip(r-4.4)RHPCBenchmark_0.1.0.zip(r-4.3)
RHPCBenchmark_0.1.0.tgz(r-4.4-any)RHPCBenchmark_0.1.0.tgz(r-4.3-any)
RHPCBenchmark_0.1.0.tar.gz(r-4.5-noble)RHPCBenchmark_0.1.0.tar.gz(r-4.4-noble)
RHPCBenchmark_0.1.0.tgz(r-4.4-emscripten)RHPCBenchmark_0.1.0.tgz(r-4.3-emscripten)
RHPCBenchmark.pdf |RHPCBenchmark.html✨
RHPCBenchmark/json (API)

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

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.02 score 21 scripts 140 downloads 48 exports 4 dependencies

Last updated 8 years agofrom:c1335a4fcb. Checks:OK: 3 NOTE: 4. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 13 2024
R-4.5-winNOTENov 13 2024
R-4.5-linuxNOTENov 13 2024
R-4.4-winNOTENov 13 2024
R-4.4-macNOTENov 13 2024
R-4.3-winOKNov 13 2024
R-4.3-macOKNov 13 2024

Exports:CholeskyAllocatorCholeskyMicrobenchmarkClaraClusteringMicrobenchmarkClusteringAllocatorCrossprodAllocatorCrossprodMicrobenchmarkDeformtransAllocatorDeformtransMicrobenchmarkDeterminantAllocatorDeterminantMicrobenchmarkEigenAllocatorEigenMicrobenchmarkGetClusteringDefaultMicrobenchmarksGetClusteringExampleMicrobenchmarksGetDenseMatrixDefaultMicrobenchmarksGetDenseMatrixExampleMicrobenchmarksGetSparseCholeskyDefaultMicrobenchmarksGetSparseCholeskyExampleMicrobenchmarksGetSparseLuDefaultMicrobenchmarksGetSparseMatrixVectorDefaultMicrobenchmarksGetSparseMatrixVectorExampleMicrobenchmarksGetSparseQrDefaultMicrobenchmarksLsfitAllocatorLsfitMicrobenchmarkMatmatAllocatorMatmatMicrobenchmarkMatvecAllocatorMatvecMicrobenchmarkPamClusteringMicrobenchmarkQrAllocatorQrMicrobenchmarkRunDenseMatrixBenchmarkRunMachineLearningBenchmarkRunSparseMatrixBenchmarkSolveAllocatorSolveMicrobenchmarkSparseCholeskyAllocatorSparseCholeskyMicrobenchmarkSparseLuAllocatorSparseLuMicrobenchmarkSparseMatrixVectorAllocatorSparseMatrixVectorMicrobenchmarkSparseQrAllocatorSparseQrMicrobenchmarkSvdAllocatorSvdMicrobenchmarkTransposeAllocatorTransposeMicrobenchmark

Dependencies:clusterlatticeMatrixmvtnorm

R HPC Benchmark

James R. McCombs

Rendered fromvignette.Rmdusingknitr::rmarkdownon Nov 13 2024.

Last update: 2017-05-23
Started: 2017-05-23

Readme and manuals

Help Manual

Help pageTopics
Allocates and initializes input to the Cholesky factorization dense matrix kernel microbenchmarksCholeskyAllocator
Conducts a single performance trial with the Cholesky factorization dense matrix kernelCholeskyMicrobenchmark
Conducts a single performance trial with the cluster::clara functionClaraClusteringMicrobenchmark
Allocates and initializes input to the clustering for machine learning microbenchmarksClusteringAllocator
This class specifies a clustering for machine learning microbenchmark.ClusteringMicrobenchmark
Computes the average of a vector of performance trial timesComputeAverageTime
Computes the standard deviation of a vector of performance trial timesComputeStandardDeviation
Allocates and populates input to the matrix cross product dense matrix kernel microbenchmarksCrossprodAllocator
Conducts a single performance trial with the matrix cross product dense matrix kernelCrossprodMicrobenchmark
Allocates and populates input to the matrix deformation and transpose dense matrix kernel microbenchmarksDeformtransAllocator
Conducts a single performance trial with the matrix deformation and transpose dense matrix kernelDeformtransMicrobenchmark
This class specifies a dense matrix microbenchmark.DenseMatrixMicrobenchmark
Allocates and populates input to the matrix determinant dense matrix kernel microbenchmarksDeterminantAllocator
Conducts a single performance trial with the matrix determinant dense matrix kernelDeterminantMicrobenchmark
Allocates and populates input to the matrix eigendecomposition kernel microbenchmarksEigenAllocator
Conducts a single performance trial with the matrix eigendecomposition dense matrix kernelEigenMicrobenchmark
Generates clusters from multivariate normal distributionsGenerateClusterData
Initializes the list of default clustering microbenchmarksGetClusteringDefaultMicrobenchmarks
Initializes the list of example clustering microbenchmarksGetClusteringExampleMicrobenchmarks
Retrieves the value of an environment variable referenced by another environment variableGetConfigurableEnvParameter
Initializes the list of default dense matrix microbenchmarksGetDenseMatrixDefaultMicrobenchmarks
Initializes the list of example dense matrix microbenchmarksGetDenseMatrixExampleMicrobenchmarks
Retrieves the number of threads from the environmentGetNumberOfThreads
Initializes the list of default sparse Cholesky factorization microbenchmarksGetSparseCholeskyDefaultMicrobenchmarks
Initializes the list of example sparse Cholesky factorization microbenchmarksGetSparseCholeskyExampleMicrobenchmarks
Initializes the list of default sparse LU factorization microbenchmarksGetSparseLuDefaultMicrobenchmarks
Initializes the list of default sparse matrix-vector microbenchmarksGetSparseMatrixVectorDefaultMicrobenchmarks
Initializes the list of example sparse matrix-vector microbenchmarksGetSparseMatrixVectorExampleMicrobenchmarks
Initializes the list of default sparse QR factorization microbenchmarksGetSparseQrDefaultMicrobenchmarks
Allocates and populates input to the matrix least squares fit dense matrix kernel microbenchmarksLsfitAllocator
Conducts a single performance trial with the matrix least squares fit dense matrix kernelLsfitMicrobenchmark
Allocates and populates input to the matrix-matrix multiplication dense matrix kernel microbenchmarksMatmatAllocator
Conducts a single performance trial with the matrix-matrix multiplication dense matrix kernelMatmatMicrobenchmark
Allocates and populates input to the matrix-vector multiplication dense matrix kernel microbenchmarksMatvecAllocator
Conducts a single performance trial with the matrix-vector multiplication dense matrix kernelMatvecMicrobenchmark
Performs microbenchmarking of a clustering for machine learning kernelMicrobenchmarkClusteringKernel
Performs microbenchmarking of a dense matrix linear algebra kernelMicrobenchmarkDenseMatrixKernel
Performs microbenchmarking of a sparse matrix linear algebra kernelMicrobenchmarkSparseMatrixKernel
Conducts a single performance trial with the cluster::pam functionPamClusteringMicrobenchmark
Performs microbenchmarking of machine learning functions specified by an input listPerformClusteringMicrobenchmarking
Performs microbenchmarking of sparse matrix kernels specified by an input listPerformSparseMatrixKernelMicrobenchmarking
Prints results of a clustering for machine learning microbenchmarkPrintClusteringMicrobenchmarkResults
Prints results of a dense matrix microbenchmarkPrintDenseMatrixMicrobenchmarkResults
Prints results of a sparse matrix microbenchmarkPrintSparseMatrixMicrobenchmarkResults
Allocates and populates input to the QR factorization dense matrix kernel microbenchmarksQrAllocator
Conducts a single performance trial with the QR factorization dense matrix kernelQrMicrobenchmark
RHPCBenchmark: A package for performance testing intrinsic R functionality and established packages relevant to high-performance computingRHPCBenchmark-package RHPCBenchmark
Runs all of the dense matrix microbenchmarksRunDenseMatrixBenchmark
Runs all of the machine learning microbenchmarksRunMachineLearningBenchmark
Runs all of the sparse matrix microbenchmarksRunSparseMatrixBenchmark
Allocates and populates input to the dense matrix kernel microbenchmark for computing the solution to a system of linear equations with multiple right-hand sidesSolveAllocator
Conducts a single performance trial with the dense matrix kernel for computing the solution to a system of linear equations with multiple right-hand sidesSolveMicrobenchmark
Allocates and initializes input to the Cholesky factorization sparse matrix kernel microbenchmarksSparseCholeskyAllocator
Conducts a single performance trial with the Cholesky factorization sparse matrix kernelSparseCholeskyMicrobenchmark
Allocates and initializes input to the LU factorization sparse matrix kernel microbenchmarksSparseLuAllocator
Conducts a single performance trial with the LU factorization sparse matrix kernelSparseLuMicrobenchmark
This class specifies a sparse matrix microbenchmark.SparseMatrixMicrobenchmark
Allocates and initializes input to the matrix-vector multiplication sparse matrix kernel microbenchmarksSparseMatrixVectorAllocator
Conducts a single performance trial with the matrix-vector multiplication sparse matrix kernelSparseMatrixVectorMicrobenchmark
Allocates and initializes input to the QR factorization sparse matrix kernel microbenchmarksSparseQrAllocator
Conducts a single performance trial with the QR factorization sparse matrix kernelSparseQrMicrobenchmark
Allocates and populates input to the singular value decomposition (SVD) dense matrix kernel microbenchmarksSvdAllocator
Conducts a single performance trial with the singular value decomposition (SVD) dense matrix kernelSvdMicrobenchmark
Allocates and populates input to the matrix transpose dense matrix kernel microbenchmarksTransposeAllocator
Conducts a single performance trial with the matrix transpose dense matrix kernelTransposeMicrobenchmark
Appends performance test results of a clustering microbenchmark to a file in CSV formatWriteClusteringPerformanceResultsCsv
Appends dense matrix performance test results to a file in CSV formatWriteDenseMatrixPerformanceResultsCsv
Appends sparse matrix performance test results to a file in CSV formatWriteSparseMatrixPerformanceResultsCsv