Exploring the performance and mapping of HPC applications to platforms in the cloud

This paper presents a scheme to optimize the mapping of HPC applications to a set of hybrid dedicated and cloud resources. First, we characterize application performance on dedicated clusters and cloud to obtain application signatures. Then, we propose an algorithm to match these signatures to resources such that performance is maximized and cost is minimized. Finally, we show simulation results revealing that in a concrete scenario our proposed scheme reduces the cost by 60% at only 10-15% performance penalty vs. a non optimized configuration. We also find that the execution overhead in cloud can be minimized to a negligible level using thin hypervisors or OS-level containers. Categories and Subject Descriptors

• Type: Journal
• Year: 2012
• Where: HPDC
• Authors: Abhishek Gupta, Laxmikant V. Kalé, Dejan S. Milojicic, Paolo Faraboschi, Richard Kaufmann, Verdi March, Filippo Gioachin, Chun Hui Suen, Bu-Sung Lee
• Keywords: Distributed And Parallel Computing, Hpc Applications, HPDC 2012, Negligible Level, Os Level