weiport.blogg.se - Project benchmark definition

#Project benchmark definition full
#Project benchmark definition software

The benchmarks then compute the average, standard deviation, maximum, and minimum run time for each microbenchmark. The top-level benchmarks execute multiple performance trials for each microbenchmark in which the run time (synonymous with wall-clock time in this document) is obtained.

RunMachineLearningBenchmark Executes the machine learning microbenchmarksĮach of these benchmark functions is a top-level function which executes microbenchmarks on several R computational kernels and other functionality relevant to each benchmark category.

RunSparseMatrixBenchmark Executes the sparse matrix microbenchmarks.

RunDenseMatrixBenchmark Executes the dense matrix microbenchmarks.

The following functions are intended to be called by users of this library to perform benchmarking for each of the three categories of benchmarks: The dense matrix linear algebra kernels, sparse matrix linear algebra kernels, and machine learning functions that are benchmarked are all part of the R interpreter’s intrinsic functionality or packages included the with the R programming environment standard distributions from CRAN. The machine learning benchmarks currently only cover variants of K-means functionality for clustering using the cluster package. The sparse linear algebra kernels are members of the R Matrix library. All of the dense linear algebra kernels are implemented around BLAS or LAPACK interfaces.

The benchmarks are divided into three categories: dense matrix linear algebra kernels, sparse matrix linear algebra kernels, and machine learning functionality. We developed the RHPCBenchmark package to determine the single-node run time performance of compute intensive linear algebra kernels that are common to many data analytics algorithms, and the run time performance of machine learning functionality commonly implemented with linear algebra operations.

#Project benchmark definition full

Optimization of the R interpreter, its intrinsic functionality, and R packages for specific hardware architectures will be necessary for data analysts to take full advantage of the latest HPC clusters, and to obviate the need to reengineer their analysis workflows.

#Project benchmark definition software

The benchmark performance results can also be used to prioritize software performance optimization efforts on emerging High Performance Computing (HPC) systems. Benchmarking is a way to assess the performance of software on a computing platform and to compare performance between different platforms.