Progress and Challenges in Extreme Scale Computing and Data - Part I of II | SIAM

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2019 SIAM Conference on Com...
Progress and Challenges in ...

Progress and Challenges in Extreme Scale Computing and Data - Part I of II

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CSE19 - MS171-1: Combining Extreme Computing and Big Data for Future Machine Learning

Presentation: John Wu, Lawrence Berkeley National Laboratory, 15 min 43 sec

CSE19 - MS171-1: Combining Extreme Computing and Big Data for Future Machine Learning

Document: CSE19 - MS171-1: Combining Extreme Computing and Big Data for Future Machine Learning

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CSE19 - MS171-2: A Scalable Randomized Singular Value Decomposition with Multiple Sketches for Big Data Analysics

Presentation: Weichung Wang, National Taiwan University, Taiwan, 23 min 47 sec

CSE19 - MS171-2: A Scalable Randomized Singular Value Decomposition with Multiple Sketches for Big Data Analysics

Document: CSE19 - MS171-2: A Scalable Randomized Singular Value Decomposition with Multiple Sketches for Big Data Analysics

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CSE19 - MS171-3: Multidisciplinary High Performance Data Analysis Forum: summary and recommendations

Presentation: Michel Dayde, University of Toulouse, France, 22 min 2 sec

CSE19 - MS171-3: Multidisciplinary High Performance Data Analysis Forum: summary and recommendations

Document: CSE19 - MS171-3: Multidisciplinary High Performance Data Analysis Forum: summary and recommendations

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CSE19 - MS171-4: Obtaining Performance from a Julia-Implementation of Trilinos Data Librairies

Presentation: Neil Lindquist, St. John's University, U.S., 12 min 21 sec

CSE19 - MS171-4: Obtaining Performance from a Julia-Implementation of Trilinos Data Librairies

Document: CSE19 - MS171-4: Obtaining Performance from a Julia-Implementation of Trilinos Data Librairies