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Exploiting Raspberry PI Clusters And Campus Lab Computers For Distributed Computing


Affiliations
1 Department of Electrical and Computer Engineering, Purdue University Fort Wayne Fort Wayne, Indiana, United States
 

Distributed computing networks harness the power of existing computing resources and grant access to significant computing power while averting the costs of a supercomputer. This work aims to configure distributed computing networks using different computer devices and explore the benefits of the computing power of such networks. First, an HTCondor pool consisting of sixteen Raspberry Pi single-board computers and one laptop is created. The second distributed computing network is set up with Windows computers in university campus labs. With the HTCondor setup, researchers inside the university can utilize the lab computers as computing resources. In addition, the HTCondor pool is configured alongside the BOINC installation on both computer clusters, allowing them to contribute to high-throughput scientific computing projects in the research community when the computers would otherwise sit idle. The scalability of these two distributed computing networks is investigated through a matrix multiplication program and the performance of the HTCondor pool is also quantified using its built-in benchmark tool. With such a setup, the limits of the distributed computing network architecture in computationally intensive problems are explored.

Keywords

Distributed Computing, Single-Board Computers, Raspberry Pi.
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  • Exploiting Raspberry PI Clusters And Campus Lab Computers For Distributed Computing

Abstract Views: 233  |  PDF Views: 109

Authors

Jacob Bushur
Department of Electrical and Computer Engineering, Purdue University Fort Wayne Fort Wayne, Indiana, United States
Chao Chen
Department of Electrical and Computer Engineering, Purdue University Fort Wayne Fort Wayne, Indiana, United States

Abstract


Distributed computing networks harness the power of existing computing resources and grant access to significant computing power while averting the costs of a supercomputer. This work aims to configure distributed computing networks using different computer devices and explore the benefits of the computing power of such networks. First, an HTCondor pool consisting of sixteen Raspberry Pi single-board computers and one laptop is created. The second distributed computing network is set up with Windows computers in university campus labs. With the HTCondor setup, researchers inside the university can utilize the lab computers as computing resources. In addition, the HTCondor pool is configured alongside the BOINC installation on both computer clusters, allowing them to contribute to high-throughput scientific computing projects in the research community when the computers would otherwise sit idle. The scalability of these two distributed computing networks is investigated through a matrix multiplication program and the performance of the HTCondor pool is also quantified using its built-in benchmark tool. With such a setup, the limits of the distributed computing network architecture in computationally intensive problems are explored.

Keywords


Distributed Computing, Single-Board Computers, Raspberry Pi.

References