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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]]
  
-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]].
  
 ===== MEADS ===== ===== MEADS =====
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   * 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.
  
-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]].
  
 === Deliverables === === Deliverables ===
  
-  * [[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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