{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,2,8]],"date-time":"2023-02-08T09:20:30Z","timestamp":1675848030217},"reference-count":8,"publisher":"IGI Global","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013,1,1]]},"abstract":"<p>High Performance Computing (HPC) applications are scientific applications that require significant CPU capabilities. They are also data-intensive applications requiring large data storage. While many researchers have examined the performance of Amazon\u2019s EC2 platform across some HPC benchmarks, an extensive study and their comparison between Amazon\u2019s EC2 and Microsoft\u2019s Windows Azure is largely missing with metrics such as memory bandwidth, I\/O performance, and communication and computational performance. The purpose of this paper is to implement existing benchmarks to evaluate and analyze these metrics for EC2 and Windows Azure that span both Infrastructure-as-a-Service and Platform-as-a-Service types. This was accomplished by running MPI versions of STREAM, Interleaved or Random (IOR) and NAS Parallel (NPB) benchmarks on small and medium instance types. In addition a new EC2 medium instance type (m1.medium) was also included in the analysis. These benchmarks measure the memory bandwidth, I\/O performance, communication and computational performance.<\/p>","DOI":"10.4018\/ijcac.2013010102","type":"journal-article","created":{"date-parts":[[2013,7,10]],"date-time":"2013-07-10T13:22:33Z","timestamp":1373462553000},"page":"13-26","source":"Crossref","is-referenced-by-count":4,"title":["Empirical Performance Analysis of HPC Benchmarks Across Variations in Cloud Computing"],"prefix":"10.4018","volume":"3","author":[{"given":"Sanjay P.","family":"Ahuja","sequence":"first","affiliation":[{"name":"School of Computing, University of North Florida, Jacksonville, FL, USA"}]},{"given":"Sindhu","family":"Mani","sequence":"additional","affiliation":[{"name":"School of Computing, University of North Florida, Jacksonville, FL, USA"}]}],"member":"2432","reference":[{"key":"ijcac.2013010102-0","unstructured":"Amedro, B., Baude, F. O., & Caromel, D. Delbe \u0301, C., Filali, I., Huet, F., \u2026 Smirnov, O. (2010). Cloud computing: Principles, systems and applications. Berlin, Germany: Springer."},{"key":"ijcac.2013010102-1","unstructured":"Department of Computer Science. (n.d.). Multiprocessor runs. Retrieved February 12, 2012, from http:\/\/www.cs.virginia.edu\/stream\/ref.html"},{"key":"ijcac.2013010102-2","unstructured":"Evangelinos, C., & Hill, C. N. (2008). Cloud computing for parallel scientific HPC applications: Feasibility of running coupled atmosphere-ocean climate models on Amazon\u2019s EC2. In Proceedings of Cloud Computing and Its Applications, ACM Workshop (CCA\u201908), New York, NY."},{"key":"ijcac.2013010102-3","doi-asserted-by":"crossref","unstructured":"Ghoshal, D., Canon, R. C., & Ramakrishnan, N. (2011). I\/O performance of virtualized cloud environments. In Proceedings of the Second International Workshop on Data Intensive Computing in the Clouds (pp. 71-80).","DOI":"10.1145\/2087522.2087535"},{"key":"ijcac.2013010102-4","unstructured":"Overview of the sample Azure service. (n.d.). Retrieved August 13, 2012, from http:\/\/msdn.microsoft.com\/en-us\/library\/hh560251(v=vs.85).aspx#BKMK_tools"},{"key":"ijcac.2013010102-5","unstructured":"The Windows Azure HPC Scheduler. (n.d.). Retrieved May 29, 2012, from http:\/\/www.paratools.com\/Azure\/HowToHPCScheduler"},{"key":"ijcac.2013010102-6","unstructured":"WhatwasStarCluster? (n.d.). Sun microsystems introduction to cloud computing architecture. Retrieved May 14, 2012, from http:\/\/web.mit.edu\/star\/cluster\/docs\/latest\/overview.html"},{"key":"ijcac.2013010102-7","doi-asserted-by":"crossref","unstructured":"Wong, C. F., Martin, R. P., Arpaci-Dusseau, R. H., & Culler, D. E. (1999). Architectural requirements and scalability of the NAS parallel benchmarks. In Proceedings of the 1999 ACM\/IEEE Conference on Supercomputing (CDROM), New York, NY.","DOI":"10.1145\/331532.331573"}],"container-title":["International Journal of Cloud Applications and Computing"],"original-title":[],"language":"ng","link":[{"URL":"https:\/\/www.igi-global.com\/viewtitle.aspx?TitleId=78515","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,2]],"date-time":"2022-06-02T02:55:20Z","timestamp":1654138520000},"score":1,"resource":{"primary":{"URL":"https:\/\/services.igi-global.com\/resolvedoi\/resolve.aspx?doi=10.4018\/ijcac.2013010102"}},"subtitle":[""],"short-title":[],"issued":{"date-parts":[[2013,1,1]]},"references-count":8,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2013,1]]}},"URL":"https:\/\/doi.org\/10.4018\/ijcac.2013010102","relation":{},"ISSN":["2156-1834","2156-1826"],"issn-type":[{"value":"2156-1834","type":"print"},{"value":"2156-1826","type":"electronic"}],"subject":[],"published":{"date-parts":[[2013,1,1]]}}}