Title: Impact of using multi-levels of parallelism on HPC applications performance hosted on Azure cloud computing

Authors: Hanan A. Hassan; Mona S. Kashkoush; Mohamed Azab; Walaa M. Sheta

Addresses: Informatics Research Institute, City of Scientific Research and Technological Applications, Egypt ' Informatics Research Institute, City of Scientific Research and Technological Applications, Egypt ' Informatics Research Institute, City of Scientific Research and Technological Applications, Egypt ' Informatics Research Institute, City of Scientific Research and Technological Applications, Egypt; CECS Department, University of Louisville, USA

Abstract: The use of high-performance computing (HPC) applications has increased progressively in scientific research and industry. Cloud computing attracts HPC users because of its extreme cost efficiency. The reduced cost is the result of the successful employment of multilayer-virtualisation enabling dynamic elastic resource-sharing between different tenants. In this paper, we evaluate the impact of using multi-levels of parallelism on computationally intensive parallel tasks hosted on a cloud virtualised HPC cluster. We use multi-levels of parallelism through a set of experiments employing both message passing and multi-threading techniques. Our evaluation addresses two main perspectives, the performance of applications and cost of running HPC applications on clouds. We use millions of operations per seconds (MOPS) and speed-up to evaluate the computational performance. To evaluate the cost we use United States Dollar/MOPS (USD/MOPS). The experiments on two different clouds are compared against each other and with published results for Amazon EC2 cloud. Results show that balancing the workload between processes and threads per process is the key factor to maintain high performance with reasonable cost.

Keywords: high performance computing; Azure cloud computing; hybrid MPI+OPENMP; NPB; NPB-MZ benchmarks.

DOI: 10.1504/IJHPCN.2019.098579

International Journal of High Performance Computing and Networking, 2019 Vol.13 No.3, pp.251 - 260

Received: 11 Jan 2017
Accepted: 24 Jul 2017
Published online: 28 Mar 2019 *

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