Monetary cost optimizations for MPI-based HPC applications on Amazon clouds: checkpoints and replicated execution

Abstract

In this paper, we propose monetary cost optimizations for MPI-based applications with deadline constraints on Amazon EC2. Particularly, we consider to utilize two kinds of Amazon EC2 instances (on-demand and spot instances). As a spot instance can fail at any time due to out-of-bid events, fault tolerant executions are necessary. Through detailed studies, we have found that two common fault tolerant mechanisms, i.e., checkpoints and replicated executions, are complementary for cost-effective MPI executions on spot instances. We formulate the optimization problem and propose a novel cost model to minimize the expected monetary cost. The experimental results with NPB benchmarks on Amazon EC2 demonstrate that 1) it is feasible to run MPI applications with performance constraints on spot instances, 2) our proposal achieves significant monetary cost reduction compared to the state-of-the-art algorithm and 3) it is necessary to adaptively choose checkpoint and replication techniques for cost-effective and reliable MPI executions on Amazon EC2.