Robert A. van de Geijn
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Robert A. van de Geijn |
Education
- B.S. in Mathematics and Computer Science (1981), University of Wisconsin-Madison
- Ph.D. in Applied Mathematics (1987), University of Maryland College Park
Work Experience
- September 2002 - present: Professor, Department of Computer Sciences, The University of Texas at Austin.
- September 1992 - present: Member, Texas Institute for Computational and Applied Mathematics, The University of Texas at Austin.
- September 1994 - August 2002: Associate Professor, Department of Computer Sciences, The University of Texas at Austin.
- September 1987 - August 1994: Assistant Professor, Department of Computer Sciences, The University of Texas at Austin.
- Aug. 1990 - May 1991: Research Professor, Computer Science Department, University of Tennessee, Knoxville.
Current Projects
- The objective of the FLAME project is to transform the development of dense linear algebra libraries from an art reserved for experts to a science that can be understood by novice and expert alike. Rather than being only a library, the project encompasses a new notation for expressing algorithms, a methodology for systematic derivation of algorithms, Application Program Interfaces (APIs) for representing the algorithms in code, and tools for mechanical derivation, implementation and analysis of algorithms and implementations.
UHM: Sparse Direct Factorizations through Unassembled Hyper-Matrices
- Coding parallel algorithms is generally regarded as a formidable task. To make this task manageable in the arena of linear algebra algorithms, we have developed the Parallel Linear Algebra Package (PLAPACK), an infrastructure for coding such algorithms at a high level of abstraction. It is often believed that by raising the level of abstraction in this fashion, performance is sacrificed. Throughout, we have maintained that indeed there is a performance penalty, but that by coding at a higher level of abstraction, more sophisticated algorithms can be implemented, which allows high levels of performance to be regained. In this paper, we show this to indeed be the case for the parallel solver package implemented using PLAPACK, which includes Cholesky, LU, and QR factorization based solvers for symmetric positive definite, general, and overdetermined systems of equations, respectively. Performance comparison with ScaLAPACK shows better performance is attained by our solvers.
Recent Selected Publications
(See also the FLAME Publication Webpage.)
Robert A. van de Geijn. Using PLAPACK: Parallel Linear Algebra Package. The MIT Press, 1997.
Robert A. van de Geijn and Enrique S. Quintana-Ortí. The Science of Programming Matrix Computations. www.lulu.com, 2008.
Field G. Van Zee, Ernie Chan, Robert van de Geijn, Enrique S. Quintana-Ortí, and Gregorio Quintana-Ortí. "Introducing: The libflame Library for Dense Matrix Computations." CiSE, to appear.