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Experimental data from the simulation of on-chip communication architectures using RedScarf simulation environment
This article presents data from an extensive set of simulation-based experiments to compare the performance of on-chip communication architectures. These experiments were performed using the RedScarf simulation environment [1], which is described in the article entitled ‘RedScarf: an open-source mul...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6849118/ https://www.ncbi.nlm.nih.gov/pubmed/31737764 http://dx.doi.org/10.1016/j.dib.2019.104725 |
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author | da Silva, Eduardo Alves Kreutz, Márcio Eduardo Zeferino, Cesar Albenes |
author_facet | da Silva, Eduardo Alves Kreutz, Márcio Eduardo Zeferino, Cesar Albenes |
author_sort | da Silva, Eduardo Alves |
collection | PubMed |
description | This article presents data from an extensive set of simulation-based experiments to compare the performance of on-chip communication architectures. These experiments were performed using the RedScarf simulation environment [1], which is described in the article entitled ‘RedScarf: an open-source multi-platform simulation environment for performance evaluation of Networks-on-Chip’ [2]. In the experiments presented here, several intra-chip communication architectures were compared under different traffic patterns. Latency, jitter, and throughput metrics were collected. Data is useful for researchers investigating on-chip communication architectures who need baseline data for comparison. |
format | Online Article Text |
id | pubmed-6849118 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-68491182019-11-15 Experimental data from the simulation of on-chip communication architectures using RedScarf simulation environment da Silva, Eduardo Alves Kreutz, Márcio Eduardo Zeferino, Cesar Albenes Data Brief Computer Science This article presents data from an extensive set of simulation-based experiments to compare the performance of on-chip communication architectures. These experiments were performed using the RedScarf simulation environment [1], which is described in the article entitled ‘RedScarf: an open-source multi-platform simulation environment for performance evaluation of Networks-on-Chip’ [2]. In the experiments presented here, several intra-chip communication architectures were compared under different traffic patterns. Latency, jitter, and throughput metrics were collected. Data is useful for researchers investigating on-chip communication architectures who need baseline data for comparison. Elsevier 2019-10-28 /pmc/articles/PMC6849118/ /pubmed/31737764 http://dx.doi.org/10.1016/j.dib.2019.104725 Text en © 2019 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Computer Science da Silva, Eduardo Alves Kreutz, Márcio Eduardo Zeferino, Cesar Albenes Experimental data from the simulation of on-chip communication architectures using RedScarf simulation environment |
title | Experimental data from the simulation of on-chip communication architectures using RedScarf simulation environment |
title_full | Experimental data from the simulation of on-chip communication architectures using RedScarf simulation environment |
title_fullStr | Experimental data from the simulation of on-chip communication architectures using RedScarf simulation environment |
title_full_unstemmed | Experimental data from the simulation of on-chip communication architectures using RedScarf simulation environment |
title_short | Experimental data from the simulation of on-chip communication architectures using RedScarf simulation environment |
title_sort | experimental data from the simulation of on-chip communication architectures using redscarf simulation environment |
topic | Computer Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6849118/ https://www.ncbi.nlm.nih.gov/pubmed/31737764 http://dx.doi.org/10.1016/j.dib.2019.104725 |
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