Title

Exploring Parallelization with a Raspberry Pi Cluster

Description/Abstract/Artist Statement

In this work, I introduce an affordable and scalable project to explore parallel computing concepts for undergraduate STEM students. A cluster computer composed of Raspberry Pis is presented along with a specific use case to explore the performance of the Pi cluster and examine the consequences of unbalanced task distribution across the cluster. The performance of the cluster is tested using both simple numerical integration and adaptive integration methods. In the case of simple integration, results show that the cluster provides speedup in accordance with expectations due to the equal time-complexity of individual computations. Adaptive integration serves as a use case to examine the importance of equitable task management across the cluster since the tasks assigned to individual threads may be of different time-complexities.

Presenting Author Name/s

Taylor Powell

Faculty Advisor/Mentor

Ayman Elmesalami, Soad Ibrahim

College Affiliation

College of Sciences

Presentation Type

Oral Presentation

Disciplines

Numerical Analysis and Scientific Computing | Programming Languages and Compilers | Theory and Algorithms

Session Title

Colleges of Sciences UG Research #3

Location

Zoom

Start Date

3-19-2022 3:30 PM

End Date

3-19-2022 4:30 PM

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Mar 19th, 3:30 PM Mar 19th, 4:30 PM

Exploring Parallelization with a Raspberry Pi Cluster

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In this work, I introduce an affordable and scalable project to explore parallel computing concepts for undergraduate STEM students. A cluster computer composed of Raspberry Pis is presented along with a specific use case to explore the performance of the Pi cluster and examine the consequences of unbalanced task distribution across the cluster. The performance of the cluster is tested using both simple numerical integration and adaptive integration methods. In the case of simple integration, results show that the cluster provides speedup in accordance with expectations due to the equal time-complexity of individual computations. Adaptive integration serves as a use case to examine the importance of equitable task management across the cluster since the tasks assigned to individual threads may be of different time-complexities.