A proactive fault tolerance approach to High Performance Computing (HPC) in the cloud

Abstract

Cloud computing offers new computing paradigms, capacity, and flexibility to high performance computing (HPC) applications with provisioning of a large number of Virtual Machines (VMs) for computation-intensive applications using the Hardware as a Service (HaaS) model. Due, however, to the large number of VMs and electronic components in HPC systems in the cloud, any fault during the execution would result in re-running the application, which will cost time, money and energy. In this paper we present a proactive Fault Tolerance (FT) approach to HPC systems in the cloud to reduce the wall clock execution time in the presence of faults. We develop a generic FT algorithm for HPC systems in the cloud. Our algorithm does not rely on a spare node prior to prediction of a failure. We analyze the dollar cost of provisioning spare nodes to assess the value of our approach. Our experimental results obtained from a real cloud execution environment show that the wall clock execution time of the computation-intensive applications in cloud can be reduced by as much as 30%. The frequency of check pointing of computation-intensive applications can be reduced to 50% with our fault tolerance approach for HPC in the cloud, compared to current FT approaches. © 2012 IEEE.