Evaluating High Performance Computing on the Windows Azure Platform

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Abstract

Using the Cloud Computing paradigm for High-Performance Computing (HPC) is currently a hot topic in the research community and the industry. The attractiveness of Cloud Computing for HPC is the capability to run large applications on powerful, scalable hardware without needing to actually own or maintain this hardware. Most current research focuses on running HPC applications on the Amazon Cloud Computing platform, which is relatively easy because it supports environments that are similar to existing HPC solutions, such as clusters and supercomputers. In this paper, we evaluate the possibility of using Microsoft Windows Azure as a platform for HPC applications. Since most HPC applications are based on the Unix programming model, their source code has to be ported to the Windows programming model in addition to porting it to the Azure platform. We outline the challenges we encountered during porting applications and their resolutions. Furthermore, we introduce a metric to measure the efficiency of Cloud Computing platforms in terms of performance and price. We compared the performance and efficiency of running these benchmarks on a real machine, an Amazon EC2 instance and a Windows Azure instance. Results show that the performance of Azure is close to the performance of running on real machines, and that it is a viable alternative for running HPC applications when compared to other Cloud Computing solutions.

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