Performance results on SAGrid for libsvm training and characterisation studies

The Support Vector Machine library has been used together with sets of data collected during the Lwazi programme at the Meraka Institute, in order to estimate the performance of the South African National Grid (SAGrid) sites in dealing with typical machine-learning tasks. Processing of standard data sets of differing sizes was done on various sites on the infrastructure, and the time needed to conclude tasks such as model training and characterisation measured. This dataset is the timing of these tasks, for varying levels of task parallelism, in order to determine the real-world performance of this application, as well as validate expectations from running similar workflows on centralised resources. This was collected in the context of one of the authors' (D. Risinamhodzi) M.Sc. thesis. Furthermore, this dataset implicitly demonstrates the functionality and performance of the CODE-RADE platform.