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High Performance Computing Student Projects

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2007 Annual Conference & Exposition


Honolulu, Hawaii

Publication Date

June 24, 2007

Start Date

June 24, 2007

End Date

June 27, 2007



Conference Session

Instrumentation and Laboratory Systems

Tagged Division

Computers in Education

Page Count


Page Numbers

12.803.1 - 12.803.17



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Paper Authors


Hassan Rajaei Bowling Green State University

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Hassan Rajaei is an Associate Professor in the Computer Science Department at Bowling Green State University.
His research interests include computer simulation, distributed and parallel simulation, performance evaluation of communication networks, wireless communications, distributed and parallel processing. Dr. Rajaei received his Ph.D. from Royal Institute of Technologies, KTH, Stockholm, Sweden and he holds an MSEE from Univ. of Utah.

Mohammad B. Dadfar is an Associate Professor in the Computer Science Department at Bowling Green State University. His research interests include Computer Extension and Analysis of Perturbation Series, Scheduling Algorithms, and Computers in Education. He currently teaches undergraduate and graduate courses in data communications, operating systems, and computer algorithms. He is a member of ACM and ASEE.

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Mohammad Dadfar Bowling Green State University

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NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract

High Performance Computing Student Projects

Hassan Rajaei and Mohammad B. Dadfar

Department of Computer Science Bowling Green State University Bowling Green, Ohio 43403 {rajaei, dadfar}


Commodity High Performance Computing (HPC) platforms such as Beowulf Clusters provide excellent opportunities to engage students with challenging projects. Courses such as parallel programming, distributed systems, operating systems, and networking can benefit from the low- cost HPC platform. In this paper we report the results on series of student projects in an advanced operating systems course which jointly have contributed to a larger group project. Several students designed, implemented, and tested segments of manageable term projects contributing to the student learning in the advance topic of high performance computing. We focused on job scheduling for a cluster of processors as the main topic, while pursuing other HPC-related areas such as parallel programming, load balancing, computer simulation, and performance analysis embedded in the theme.

In this paper we examine following scheduling polices: FCFS (First-Come-First-Serve), Backfilling Algorithms (Aggressive, Conservative, Multiple Queue, Look-ahead), Co- scheduling, and Gang Scheduling. While most of the scheduling policies are batch, Gang Scheduling provides a timesharing approach to the multiprocessor system. Our results indicate that Gang scheduling offers an attractive solution to the drawbacks of batch scheduling. This is especially true with respect to the response time and overestimation of the processing time of the submitted jobs in the system.

1. Introduction

High performance computing offers an excellent vehicle to accelerate computational needs of scientific and engineering applications. This platform currently can easily be configured with clusters of PCs connected through a high-speed switch on a high-speed network. Such a tool provides exceptional opportunities to explore numerous projects for educational as well as research purposes. We have installed a Beowulf Cluster1 with 16 compute-nodes in our computing lab, and have engaged our students with exciting projects in courses such as Operating Systems, Communication Networks, Parallel Programming, Distributed Simulation, Algorithms, Data Base Management, and several others. Within a short period of time, we have witnessed considerable increase in student projects in our HPC lab with several success stories2, 3 . Student interest and their reported success are growing. They are excited to work with advanced and practical problems which take them beyond the theory of their textbooks.

Rajaei, H., & Dadfar, M. (2007, June), High Performance Computing Student Projects Paper presented at 2007 Annual Conference & Exposition, Honolulu, Hawaii. 10.18260/1-2--2804

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