Computes the standard deviation of a vector of performance trial times
Allocates and populates input to the matrix cross product dense matrix kernel
This class specifies a clustering for machine learning microbenchmark.
Computes the average of a vector of performance trial times
GetClusteringExampleMicrobenchmarks
Initializes the list of example clustering microbenchmarks
GetConfigurableEnvParameter
Retrieves the value of an environment variable referenced by another
Generates clusters from multivariate normal distributions
GetClusteringDefaultMicrobenchmarks
Initializes the list of default clustering microbenchmarks
GetDenseMatrixDefaultMicrobenchmarks
Initializes the list of default dense matrix microbenchmarks
GetDenseMatrixExampleMicrobenchmarks
Initializes the list of example dense matrix microbenchmarks
PamClusteringMicrobenchmark
Conducts a single performance trial with the cluster::pam function
PerformClusteringMicrobenchmarking
Performs microbenchmarking of machine learning functions specified by an
ClaraClusteringMicrobenchmark
Conducts a single performance trial with the cluster::clara function
Allocates and initializes input to the clustering for machine learning
DeformtransMicrobenchmark
Conducts a single performance trial with the matrix deformation and transpose
DenseMatrixMicrobenchmark
This class specifies a dense matrix microbenchmark.
GetSparseCholeskyExampleMicrobenchmarks
Initializes the list of example sparse Cholesky factorization
Allocates and initializes input to the Cholesky factorization dense matrix
Conducts a single performance trial with the Cholesky factorization dense
Allocates and populates input to the matrix determinant dense matrix kernel
DeterminantMicrobenchmark
Conducts a single performance trial with the matrix determinant dense
Conducts a single performance trial with the matrix cross product dense
Allocates and populates input to the matrix deformation and transpose dense
Allocates and populates input to the matrix eigendecomposition kernel
Conducts a single performance trial with the matrix eigendecomposition dense
GetSparseQrDefaultMicrobenchmarks
Initializes the list of default sparse QR factorization microbenchmarks
Allocates and populates input to the matrix least squares fit dense matrix
Conducts a single performance trial with the matrix least squares fit dense
Allocates and populates input to the matrix-matrix multiplication dense
GetSparseMatrixVectorDefaultMicrobenchmarks
Initializes the list of default sparse matrix-vector microbenchmarks
GetSparseMatrixVectorExampleMicrobenchmarks
Initializes the list of example sparse matrix-vector microbenchmarks
MicrobenchmarkDenseMatrixKernel
Performs microbenchmarking of a dense matrix linear algebra kernel
MicrobenchmarkSparseMatrixKernel
Performs microbenchmarking of a sparse matrix linear algebra kernel
Conducts a single performance trial with the singular value decomposition
Allocates and populates input to the matrix transpose dense matrix kernel
GetSparseLuDefaultMicrobenchmarks
Initializes the list of default sparse LU factorization microbenchmarks
Conducts a single performance trial with the matrix-matrix multiplication
Allocates and populates input to the matrix-vector multiplication dense
RunMachineLearningBenchmark
Runs all of the machine learning microbenchmarks
Runs all of the sparse matrix microbenchmarks
Allocates and populates input to the dense matrix kernel microbenchmark
Conducts a single performance trial with the dense matrix kernel for
PrintDenseMatrixMicrobenchmarkResults
Prints results of a dense matrix microbenchmark
PrintSparseMatrixMicrobenchmarkResults
Prints results of a sparse matrix microbenchmark
SparseMatrixMicrobenchmark
This class specifies a sparse matrix microbenchmark.
SparseMatrixVectorAllocator
Allocates and initializes input to the matrix-vector multiplication sparse
Retrieves the number of threads from the environment
GetSparseCholeskyDefaultMicrobenchmarks
Initializes the list of default sparse Cholesky factorization
PerformSparseMatrixKernelMicrobenchmarking
Performs microbenchmarking of sparse matrix kernels specified by an input
PrintClusteringMicrobenchmarkResults
Prints results of a clustering for machine learning microbenchmark
Allocates and initializes input to the Cholesky factorization sparse
SparseCholeskyMicrobenchmark
Conducts a single performance trial with the Cholesky factorization
WriteDenseMatrixPerformanceResultsCsv
Appends dense matrix performance test results to a file in CSV format
WriteSparseMatrixPerformanceResultsCsv
Appends sparse matrix performance test results to a file in CSV format
Allocates and populates input to the QR factorization dense matrix kernel
Conducts a single performance trial with the QR factorization dense matrix
SparseMatrixVectorMicrobenchmark
Conducts a single performance trial with the matrix-vector multiplication
Allocates and initializes input to the QR factorization sparse matrix kernel
Conducts a single performance trial with the matrix transpose dense matrix
WriteClusteringPerformanceResultsCsv
Appends performance test results of a clustering microbenchmark to a file in
Conducts a single performance trial with the matrix-vector multiplication
MicrobenchmarkClusteringKernel
Performs microbenchmarking of a clustering for machine learning kernel
RHPCBenchmark: A package for performance testing intrinsic R functionality
Runs all of the dense matrix microbenchmarks
Allocates and initializes input to the LU factorization sparse matrix kernel
Conducts a single performance trial with the LU factorization sparse matrix
Conducts a single performance trial with the QR factorization sparse matrix
Allocates and populates input to the singular value decomposition (SVD) dense