Execution time prediction for grid infrastructures based on runtime provenance data
WORKS '13 Proceedings of the 8th Workshop on Workflows in Support of Large-Scale Science
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We present statistical techniques for predicting the queue times experienced by jobs submitted to a space-sharing parallel machine with first-come-first-served (FCFS) scheduling. We apply these techniques to trace data from the Intel Paragon at the San Diego Supercomputer Center and the IBM SP2 at the Cornell Theory Center. We show that it is possible to predict queue times with accuracy that is acceptable. A later version of this technical report has been published in the Proceedings of the 11th IEEE International Parallel Processing Symposium (IPPS ''97), and is available from http://www.sdsc.edu/~downey/predicting/