Benchmarks for High-Performance Computing Environments
Appends dense matrix performance test results to a file in CSV format
Allocates and initializes input to the Cholesky factorization dense ma...
Conducts a single performance trial with the Cholesky factorization de...
Conducts a single performance trial with the cluster::clara function
Allocates and initializes input to the clustering for machine learning...
This class specifies a clustering for machine learning microbenchmark.
Computes the average of a vector of performance trial times
Computes the standard deviation of a vector of performance trial times
Allocates and populates input to the matrix cross product dense matrix...
Conducts a single performance trial with the matrix cross product dens...
Allocates and populates input to the matrix deformation and transpose ...
Conducts a single performance trial with the matrix deformation and tr...
This class specifies a dense matrix microbenchmark.
Allocates and populates input to the matrix determinant dense matrix k...
Conducts a single performance trial with the matrix determinant dense ...
Allocates and populates input to the matrix eigendecomposition kernel ...
Conducts a single performance trial with the matrix eigendecomposition...
Generates clusters from multivariate normal distributions
Initializes the list of default clustering microbenchmarks
Initializes the list of example clustering microbenchmarks
Retrieves the value of an environment variable referenced by another e...
Initializes the list of default dense matrix microbenchmarks
Initializes the list of example dense matrix microbenchmarks
Retrieves the number of threads from the environment
Initializes the list of default sparse Cholesky factorization microben...
Initializes the list of example sparse Cholesky factorization microben...
Initializes the list of default sparse LU factorization microbenchmark...
Initializes the list of default sparse matrix-vector microbenchmarks
Initializes the list of example sparse matrix-vector microbenchmarks
Initializes the list of default sparse QR factorization microbenchmark...
Allocates and populates input to the matrix least squares fit dense ma...
Conducts a single performance trial with the matrix least squares fit ...
Allocates and populates input to the matrix-matrix multiplication dens...
Conducts a single performance trial with the matrix-matrix multiplicat...
Allocates and populates input to the matrix-vector multiplication dens...
Conducts a single performance trial with the matrix-vector multiplicat...
Performs microbenchmarking of a clustering for machine learning kernel
Performs microbenchmarking of a dense matrix linear algebra kernel
Performs microbenchmarking of a sparse matrix linear algebra kernel
Conducts a single performance trial with the cluster::pam function
Performs microbenchmarking of machine learning functions specified by ...
Performs microbenchmarking of sparse matrix kernels specified by an in...
Prints results of a clustering for machine learning microbenchmark
Prints results of a dense matrix microbenchmark
Prints results of a sparse matrix microbenchmark
Allocates and populates input to the QR factorization dense matrix ker...
Conducts a single performance trial with the QR factorization dense ma...
RHPCBenchmark: A package for performance testing intrinsic R functiona...
Runs all of the dense matrix microbenchmarks
Runs all of the machine learning microbenchmarks
Runs all of the sparse matrix microbenchmarks
Allocates and populates input to the dense matrix kernel microbenchmar...
Conducts a single performance trial with the dense matrix kernel for c...
Allocates and initializes input to the Cholesky factorization sparse m...
Conducts a single performance trial with the Cholesky factorization sp...
Allocates and initializes input to the LU factorization sparse matrix ...
Conducts a single performance trial with the LU factorization sparse m...
This class specifies a sparse matrix microbenchmark.
Allocates and initializes input to the matrix-vector multiplication sp...
Conducts a single performance trial with the matrix-vector multiplicat...
Allocates and initializes input to the QR factorization sparse matrix ...
Conducts a single performance trial with the QR factorization sparse m...
Allocates and populates input to the singular value decomposition (SVD...
Conducts a single performance trial with the singular value decomposit...
Allocates and populates input to the matrix transpose dense matrix ker...
Conducts a single performance trial with the matrix transpose dense ma...
Appends performance test results of a clustering microbenchmark to a f...
Appends sparse matrix performance test results to a file in CSV format
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.