SeeMore: A kinetic parallel computer sculpture for educating broad audiences on parallel computation
We discuss the design, implementation, and evaluation of a 256-node Raspberry-Pi cluster with kinetic properties. Each compute node is attached to a servo mechanism such that movement results from local computation. The result is SeeMore, a kinetic parallel computer sculpture designed to enable visu...
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| Veröffentlicht in: | Journal of parallel and distributed computing Jg. 105; S. 183 - 199 |
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| Hauptverfasser: | , , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Elsevier Inc
01.07.2017
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| Schlagworte: | |
| ISSN: | 0743-7315, 1096-0848 |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | We discuss the design, implementation, and evaluation of a 256-node Raspberry-Pi cluster with kinetic properties. Each compute node is attached to a servo mechanism such that movement results from local computation. The result is SeeMore, a kinetic parallel computer sculpture designed to enable visualization of parallel algorithms in an effort to educate broad audiences as to the beauty, complexity, and importance of parallel computation. The algorithms and interfaces were implemented by students from various related courses at VA Tech. We describe these designs in sufficient detail to enable others to build their own kinetic computing sculptures to augment their experiential learning programs. Our evaluations at exhibitions indicate 63% and 84% of visitors enjoyed interacting with SeeMore while 69% and 87% believed SeeMore has educational value.
•Design of SeeMore, a kinetic parallel computer sculpture for educating broad audiences on parallel computation by visualization, is presented.•Hardware implementation and software interfaces design are discussed.•Those parallel algorithms that are heavily used by the community and compelling for visualization are identified.•Evaluation of the survey of exhibitions demonstrates that kinetic visualization of parallel computation can impart a basic understanding of parallel computation to very broad audiences. |
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| ISSN: | 0743-7315 1096-0848 |
| DOI: | 10.1016/j.jpdc.2017.01.017 |