Empirical Evaluation of PDES Execution on Cloud and Virtual Machine Platforms

Abstract

Virtual machine (VM) technologies, especially those offered via Cloud platforms, present new dimensions with respect to performance and cost in executing parallel discrete event simulation (PDES) applications. Due to the introduction of overall cost as a metric, the choice of the highest-end computing configuration is no longer the most economical one. Moreover, runtime dynamics unique to VM platforms introduce new performance characteristics, and the variety of possible VM configurations give rise to a range of choices for hosting a PDES run. Here, an empirical study of these issues is undertaken to guide an understanding of the dynamics, trends and trade-offs in executing PDES on VM/Cloud platforms. Performance results and cost measures are obtained from actual execution of a range of scenarios in two PDES benchmark applications on the Amazon Cloud offerings and on a high-end VM host machine. The data reveals interesting insights into the new VM-PDES dynamics that come into play and also leads to counter-intuitive guidelines with respect to choosing the best and second-best configurations when overall cost of execution is considered. In particular, it is found that choosing the highest-end VM configuration guarantees neither the best runtime nor the least cost. Interestingly, choosing a (suitably scaled) low-end VM configuration provides the least overall cost without adversely affecting the total runtime.