RHPCBenchmark (version 0.1.0)

ClusteringMicrobenchmark: This class specifies a clustering for machine learning microbenchmark.

Description

This class specifies a clustering for machine learning microbenchmark.

Fields

active

a logical indicating whether the microbenchmark is to be executed (TRUE) or not (FALSE).

benchmarkName

a character string that is the name of the microbenchmark.

benchmarkDescription

a character string describing the microbenchmark.

dataObjectName

a character string specifying the name of the data object that is input to the benchmark; the object must be stored in the R data file with the same base name and a .RData extension. Setting the field to NA_character_ indicates that the test data will be dynamically generated by the function given in the allocatorFunction field instead of read from a data file.

numberOfFeatures

the number features; this value must match the number of features in the data set given by the field dataObjectName unless the field is populated with NA_character_.

numberOfClusters

the number of clusters in the data set; this value must match the number of clusters in the data set given by the field dataObjectName unless the field is populated with NA_character_.

numberOfFeatureVectorsPerCluster

the number of feature vectors per cluster; this value must match the number of clusters in the data set given by the field dataObjectName unless the field is populated with NA_character_.

numberOfTrials

an integer specifying the number of performance trials conducted on the data set to be tested.

numberOfWarmupTrials

an integer specifying the number of warmup trials to be conducted on the data set.

allocatorFunction

the function that allocates and initializes input to the benchmark function. The function takes a ClusteringMicrobenchmark object. For clustering benchmarks, the allocator function should return a list containing the following items:

featureVectors

a matrix, the rows of which are the feature vectors

numberOfFeatures

an integer indicating the number of features

numberOfFeatureVectors

an integer indicating the number of feature vectors

numberOfClusters

an integer indicating the number of clusters in the data set

benchmarkFunction

the benchmark function which executes the functionality to be timed. The function takes a SparseMatrixMicrobenchmark and a list of kernel parameters returned by the allocator function.