PrintClusteringMicrobenchmarkResults: Prints results of a clustering for machine learning...
In RHPCBenchmark: Benchmarks for High-Performance Computing Environments

PrintClusteringMicrobenchmarkResults prints performance results for a clustering for machine learning microbenchmark to standard output in a format that is easily human readable

PrintClusteringMicrobenchmarkResults(benchmarkName, numberOfThreads,
  numberOfFeatures, numberOfFeatureVectors, numberOfClusters,
  numberOfSuccessfulTrials, trialTimes, averageWallClockTimes,
  standardDeviations)

`benchmarkName`	character string specifying the name of the microbenchmark
`numberOfThreads`	the number of threads all of the performance trials were conducted with
`numberOfFeatures`	the number of features, i.e. the dimension of the feature vector
`numberOfFeatureVectors`	the number of feature vectors in the data set
`numberOfClusters`	the number of clusters in the data set
`numberOfSuccessfulTrials`	an integer vector specifying the number of performance trials that were successfully performed for each data set
`trialTimes`	a real matrix with each column containing the run times of all of the successful performance trials associated with a particular data set. The number of valid entries in each column are specified by the entries in the `numberOfSuccessfulTrials` vector
`averageWallClockTimes`	a vector of average wall clock times computed for each matrix tested during the performance trials
`standardDeviations`	a vector of standard deviations of the wall clock times obtained for each matrix tested during the performance trials

This function prints the performance results obtained by a clustering for machine learning microbenchmark. Summary run time performance statistics for each clustering data set tested are computed and printed. The summary statistics include the minimum, maximum, average, and standard deviation of the wall clock times obtained by the performance trials with respect to each data tested.

RHPCBenchmark documentation built on May 2, 2019, 6:40 a.m.