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Gustavo Chávez

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Gustavo Chávez
Postdoctoral Fellow
Computational Research Division
Lawrence Berkeley National Laboratory
1 Cyclotron Road
MS 50A-3111
Berkeley, CA 94720 US

Bio

Gustavo Chávez is a postdoctoral fellow at the scalable solvers group at the Lawrence Berkeley National Laboratory, funded by the U.S. Department of Energy through the Exascale Computing Project.

His research is in Computational Science & Engineering at extreme scale, primarily through the development and support of the Structured Matrix Package: STRUMPACK.

He received a Ph.D. in Computer Science under supervision of Prof. David Keyes and a M.Sc. in Applied Mathematics from the King Abdullah University of Science and Technology (KAUST), and a B.Eng. in Software Engineering from the Universidad Tecnológica de México.​


Publications


Research activities

  • High-performance linear solvers based on hierarchical matrices.
  • Approximate factorizations of kernel matrices for high-dimensional data.

2018 talks

> June 18th, 2018. Berkeley CA, USA. The 13th Scheduling For Large Scale Systems WorkshopA Study of Clustering Techniques and Hierarchical Matrix Formats for Kernel Ridge Regression.

> May 21th, 2018. Vancouver, Canada. IPDPS Workshop on Parallel and Distributed Computing for Large-Scale Machine Learning and Big Data Analytics. A Study of Clustering Techniques and Hierarchical Matrix Formats for Kernel Ridge Regression.

March 8th, 2018. Tokyo, Japan. Minisymposium: Hierarchical Low-Rank Approximation Methods / 18th SIAM Conference on Parallel Processing for Scientific Computing (PP18). Hierarchical matrix preconditioners on distributed memory environments. (slides)

> February 7th  2018. Knoxville TN, USA. Exascale Computing Project ECP Annual Meeting. Poster: STRUMPACK.