High Performance Computing Applications In Cloud Research Articles

Evaluating and Improving the Performance and Scheduling of HPC Applications in Cloud

Cloud computing is emerging as a promising alternative to supercomputers for some high-performance computing (HPC) applications. With cloud as an additional deployment option, HPC users and providers are faced with the challenges of dealing with highly heterogeneous resources, where the variability spans across a wide range of processor configurations, interconnects, virtualization environments, and pricing models. In this paper, we take a holistic viewpoint to answer the question— why and who should choose cloud for HPC, for what applications, and how should cloud be used for HPC? To this end, we perform comprehensive performance and cost evaluation and analysis of running a set of HPC applications on a range of platforms, varying from supercomputers to clouds. Further, we improve performance of HPC applications in cloud by optimizing HPC applications’ characteristics for cloud and cloud virtualization mechanisms for HPC. Finally, we present novel heuristics for online application-aware job scheduling in multi-platform environments. Experimental results and simulations using CloudSim show that current clouds cannot substitute supercomputers but can effectively complement them. Significant improvement in average turnaround time (up to 2X)and throughput (up to 6X) can be attained using our intelligent application-aware dynamic scheduling heuristics compared tosingle-platform or application-agnostic scheduling.

Improving HPC Application Performance in Public Cloud

Improving as well as evaluating the performance of High Performance Computing (HPC) applications by migrating them to Cloud environments are widely considered as critical issues in the field of high performance and Cloud computing. However, poor network performance, heterogeneous and dynamic environments are some series of pitfalls for execution of HPC applications in Cloud. This paper proposes a new approach to improve the performance and scalability of HPC applications on Amazon's HPC Cloud. The evidence from our approach points a significant improvement in speed up and scale up with the response rate of more than 20 percent parallel efficiency on the Cloud in comparison to dedicated HPC cluster. We state that the EC2 Cloud system is a feasible platform for deploying on-demand, small sized HPC applications.