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| projects [2019/08/30 14:08] – Jaroslaw Zola | projects [2019/08/30 15:12] – Jaroslaw Zola |
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| [[https://www.nsf.gov/awardsearch/showAward?AWD_ID=1910193|CNS Core: Small: Rethinking the Software Architecture for Mobile DNA Analysis]] | [[https://www.nsf.gov/awardsearch/showAward?AWD_ID=1910193|CNS Core: Small: Rethinking the Software Architecture for Mobile DNA Analysis]] |
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| To learn more, please visit the official project web page [[http://www.score-group.org/doku.php?id=SMARTEn]]. | **To learn more, please visit the official project web page:** [[http://www.score-group.org/doku.php?id=SMARTEn]]. |
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| ===== MEADS ===== | ===== MEADS ===== |
| * Development of end-to-end solutions for cutting-edge applications in advanced manufacturing. | * Development of end-to-end solutions for cutting-edge applications in advanced manufacturing. |
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| To learn more, please visit the official project web page [[https://github.com/ubdsgroup/meads]]. | **To learn more, please visit the official project web page:** [[https://github.com/ubdsgroup/meads]]. |
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| === Deliverables === | === Deliverables === |
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| * [[https://gitlab.com/SCoRe-Group/APSPark|APSPark]] Efficient and scalable All-Pairs Shortest-Path Solver for Apache Spark. On a modest Spark cluster (e.g., 1024 Intel Xeon cores), the solver can handle arbitrary undirected graphs with over 200,000 vertices. | * [[https://gitlab.com/SCoRe-Group/APSPark|APSPark]] is efficient and scalable All-Pairs Shortest-Path Solver for Apache Spark. On a modest Spark cluster (e.g., 1024 Intel Xeon cores), the solver can handle arbitrary undirected graphs with over 200,000 vertices. |
| * [[https://gitlab.com/SCoRe-Group/IsomapSpark/|IsomapSpark]] is a tool to efficiently learn manifolds from large-scale high-dimensional data. The method is based on Isomap spectral dimensionality reduction and is implemented entirely in Apache Spark. | * [[https://gitlab.com/SCoRe-Group/IsomapSpark/|IsomapSpark]] is a tool to efficiently learn manifolds from large-scale high-dimensional data. The method is based on Isomap spectral dimensionality reduction and is implemented entirely in Apache Spark. |
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