Impact of Process Allocation Strategies in High Performance Cloud Computing on Azure Platform

Abstract

Nowadays, there is an increasing demand in the High-Performance Computing (HPC) community to make use of different public cloud service provider. The question of which cloud provider is superior for a certain application and usage configuration is very important for the successful deployment of HPC application on the cloud. In this paper, we evaluate the performance of HPC applications on Microsoft Azure cloud platform using the well-known NAS parallel benchmarks. These benchmarks are considered as examples of general scientific HPC applications to test the communication performance. Different process allocation strategies are performed in terms of MOPS and Speedup. Our results show that allocating one process per instance achieves higher scalability at the expense of the cost. The results compared with the same results with the same experiments in Amazon platform. We found that Azure platform has better shared-memory communication performance than Amazon platform. In contrast, Amazon is superior to Azure platform in terms of Ethernet bandwidth.