Experiences with Cost and Utility Trade-offs on IaaS Clouds, Grids, and On-Premise Resources

Abstract

Cloud computing is now a mainstream technology in many application domains and user constituencies. For scientific high-performance applications in academic and research settings however, the trade-offs between cost and elasticity on the one hand, and performance and access on the other, is not always clear. We discuss our experiences with comparing cost and utility for a hemodynamics computational fluid dynamics code on three typical platform-types available to researchers: IaaS clouds, grids, and on-premise local resources. To rank the tested platforms, we introduce a simple utility function describing the value of a completed computational task to the user as a function of the wait time and the cost of the computation. Our results suggest that IaaS clouds can be a convenient choice for the considered class of CFD simulations, providing a valuable trade-off between cost and task completion time.