Empirical Performance Analysis of HPC Benchmarks Across Variations in Cloud Computing

Abstract

High Performance Computing (HPC) applications are scientific applications that require significant CPU capabilities. They are also data-intensive applications requiring large data storage. While many researchers have examined the performance of Amazon’s EC2 platform across some HPC benchmarks, an extensive study and their comparison between Amazon’s EC2 and Microsoft’s Windows Azure is largely missing with metrics such as memory bandwidth, I/O performance, and communication and computational performance. The purpose of this paper is to implement existing benchmarks to evaluate and analyze these metrics for EC2 and Windows Azure that span both Infrastructure-as-a-Service and Platform-as-a-Service types. This was accomplished by running MPI versions of STREAM, Interleaved or Random (IOR) and NAS Parallel (NPB) benchmarks on small and medium instance types. In addition a new EC2 medium instance type (m1.medium) was also included in the analysis. These benchmarks measure the memory bandwidth, I/O performance, communication and computational performance.