An Interference-Aware Strategy for Co-locating High Performance Computing Applications in Clouds

Cross-interference may happen when applications share a common physical machine, affecting negatively their performances. This problem occurs frequently when high performance applications are executed in clouds. Some papers of the related literature have considered this problem when proposing strategies for Virtual Machine Placement. However, they neither have employed a suitable method for predicting interference nor have considered the minimization of the number of used physical machines and interference at the same time. In this paper, we present a solution based on the Iterated Local Search framework to solve the Interference-aware Virtual Machine Placement Problem for HPC applications in Clouds (IVMP). This problem aims to minimize, at the same time, the interference suffered by HPC applications which share common physical machines and the number of physical machines used to allocate them. Experiments were conducted in a real scenario by using applications from oil and gas industry and applications from the HPCC benchmark. They showed that our method reduced interference in more than 40%, using the same number of physical machines of the most widely employed heuristics to solve the problem.