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HPC as a Service in Education

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Conference

2016 ASEE Annual Conference & Exposition

Location

New Orleans, Louisiana

Publication Date

June 26, 2016

Start Date

June 26, 2016

End Date

August 28, 2016

ISBN

978-0-692-68565-5

ISSN

2153-5965

Conference Session

Curricular Issues in Computing and Information Technology Programs I

Tagged Division

Computing & Information Technology

Tagged Topic

Diversity

Page Count

14

DOI

10.18260/p.25497

Permanent URL

https://peer.asee.org/25497

Download Count

198

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Paper Authors

biography

Hassan Rajaei Bowling Green State University

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Hassan Rajaei is a professor of computer science at Bowling Green State University, Ohio. His research interests include cloud computing, High Performance Computing (HPC), distributed simulation, parallel and distributed processing, communication networks, wireless communications, and virtual training environments. Rajaei received his Ph.D. from Royal Institute of Technology, KTH, Stockholm, Sweden, and he holds a M.S.E.E. from the University of Utah, and a BS from University of Tehran.

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Saba Jamalian Bowling Green State University

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Abstract

Abstract- Advances in Cloud Computing have opened many chapters in Information Technology. Numerous service platforms offer clients of the cloud ease of use and flexibility using the provided services. Education with billions of potential users worldwide is a major target. An emerging service called HPC-as-a-Service (HPCaaS) targets Science, Technology, Engineering, and Math (STEM) users. In this paper we discuss the use of HPCaaS in STEM education.

Cloud Computing provides unique benefits such as resource pooling, cost efficiency, availability, and large computational power. These features have attracted scientists, engineers, and scholars, as well as the High Performance Computing (HPC) users and students. HPC programs often consume large number of collaborating processors to reduce the execution time, where synchronization between these processors and the communication overhead among them can become real challenge even on dedicated special hardware. As a result, moving HPC applications to the cloud can adversely impact the above difficulties with additional issues, primarily virtualization, multi-tenancy, and network latency. The solution tends to be the emerging trend for a new cloud service known as HPC-as-a-Service.

Cloud enables the HPC users to have access to supercomputing resources on demand and in a cost efficient manner. The providers of HPCaaS, often own the service platform, administrate, and maintain the virtual resources. They can either own the hardware or rent it from a cloud service provider. As a result, the platform can have updated resources with the latest technology while the users can benefit the service and need not worry about the underlying mechanisms.

In this paper, we present a HPCaaS platform called ASETS, which uses Software Defined Networking (SDN) technologies to smooth the execution of parallel tasks in the cloud. Further, we provide several application examples that could be used in a typical introductory parallel programing course. We argue that HPCaaS platform like ASETS, significant benefits to the users of HPC on the cloud. This is especially true for students and educators which do not need to deal for the underlying complexities of the cloud. Our solution makes it possible for the HPC applications (e.g. Scientific & Engineering complex problems, to Defense, Finance, Pharmaceutical, and Big Data) to enjoy using the cloud services and yet gain good performance. Finally, we provide execution performance of the given examples both on a private cloud as well as executing them on Amazon public cloud. We conclude that HPCaaS platform can greatly facilitate learning capabilities of students especially in institutions who may not have access to a local high performance committing or private cloud.

Rajaei, H., & Jamalian, S. (2016, June), HPC as a Service in Education Paper presented at 2016 ASEE Annual Conference & Exposition, New Orleans, Louisiana. 10.18260/p.25497

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