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Issue No. 05 - Sept.-Oct. (2016 vol. 18)
ISSN: 1521-9615
pp: 68-77
Cole Freniere , University of Massachusetts Dartmouth
Ashish Pathak , University of Massachusetts Dartmouth
Mehdi Raessi , University of Massachusetts Dartmouth
Gaurav Khanna , University of Massachusetts Dartmouth
The feasibility of running MPI-parallel, GPU-accelerated, multiphase flow simulations on Amazon's Elastic Compute Cloud (EC2) service is evaluated as an alternative computational resource. A cloud cluster on Amazon EC2 is compared to a conventional local high-performance computing cluster in terms of performance and cost. The steps necessary to set up a cloud cluster and acquire the appropriate hardware and software stacks are outlined. The incompressible multiphase flow solver is benchmarked on both cloud and local clusters by performing strong and weak scaling analyses. Amazon's EC2 service is competitive with the local cluster in a certain range of simulations, but there are some performance limitations, particularly in its GPU card performance and cluster network connection, which negatively impact the parallel simulations presented herein. Finally, Amazon's EC2 service is studied from an economic perspective and compared with a conventional local cluster.
Flow control, Simulations, Computational modeling, Benchmark testing, Graphics processing units, Cloud computing, High performance computing, Heterogeneious networks, Scientific computing

C. Freniere, A. Pathak, M. Raessi and G. Khanna, "The Feasibility of Amazon's Cloud Computing Platform for Parallel, GPU-Accelerated, Multiphase-Flow Simulations," in Computing in Science & Engineering, vol. 18, no. 5, pp. 68-77, 2016.
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