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- Fred G. Gustavson

Discipline name
H-index
Citations
Publications
World Ranking
National Ranking

Computer Science
D-index
30
Citations
5,763
98
World Ranking
8254
National Ranking
65

- Algebra
- Algorithm
- Programming language

The scientist’s investigation covers issues in Linear algebra, Algorithm, Parallel computing, Sparse approximation and Matrix-free methods. The various areas that Fred G. Gustavson examines in his Linear algebra study include Fortran, Recursion, System of linear equations, Computation and Cholesky decomposition. The concepts of his Algorithm study are interwoven with issues in Multiplication and Memory hierarchy.

His study on Parallel computing is mostly dedicated to connecting different topics, such as Central processing unit. His Sparse approximation research integrates issues from Sparse matrix and Coefficient matrix. To a larger extent, he studies Matrix with the aim of understanding Sparse matrix.

- Fast solution of toeplitz systems of equations and computation of Padé approximants (349 citations)
- The Sparse Tableau Approach to Network Analysis and Design (273 citations)
- Two Fast Algorithms for Sparse Matrices: Multiplication and Permuted Transposition (271 citations)

Parallel computing, Algorithm, Matrix, Cholesky decomposition and Linear algebra are his primary areas of study. The study incorporates disciplines such as Computation, Basic Linear Algebra Subprograms and Subroutine in addition to Parallel computing. His Algorithm research is multidisciplinary, incorporating elements of Multiplication, Numerical linear algebra, Data structure and Matrix calculus.

His Matrix research is multidisciplinary, relying on both Structure and Square. His Cholesky decomposition research is multidisciplinary, incorporating perspectives in Factorization, Symmetric matrix and Fortran. The Linear algebra study combines topics in areas such as Theoretical computer science, Multi-core processor and Implementation.

- Parallel computing (47.10%)
- Algorithm (39.13%)
- Matrix (38.41%)

- Parallel computing (47.10%)
- Algorithm (39.13%)
- Cholesky decomposition (26.81%)

His scientific interests lie mostly in Parallel computing, Algorithm, Cholesky decomposition, Matrix and Factorization. His research integrates issues of ScaLAPACK and Linear algebra in his study of Parallel computing. Algorithm connects with themes related to Data structure in his study.

His Cholesky decomposition study combines topics in areas such as Symmetric matrix, Basic Linear Algebra Subprograms and Fortran. His Fortran research incorporates themes from Software, Computation and Hermitian matrix. His Matrix research focuses on Parallelism and how it connects with Space, Square and Set.

- An experimental comparison of cache-oblivious and cache-conscious programs (76 citations)
- Parallel and Cache-Efficient In-Place Matrix Storage Format Conversion (55 citations)
- Method and structure of using simd vector architectures to implement matrix multiplication (19 citations)

- Algebra
- Algorithm
- Programming language

Fred G. Gustavson mostly deals with Parallel computing, Algorithm, Data structure, Software and Parallel algorithm. His work in the fields of Cache overlaps with other areas such as Load balancing. His Cholesky decomposition research extends to Algorithm, which is thematically connected.

His biological study spans a wide range of topics, including Transformation, Structure, Representation and Matrix. Fred G. Gustavson combines subjects such as Structure, Matrix multiplication and SIMD with his study of Software. His Parallel algorithm study combines topics from a wide range of disciplines, such as Synchronization, Overhead, Distributed memory and Information and Computer Science.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Fast solution of toeplitz systems of equations and computation of Padé approximants

Richard P Brent;Fred G Gustavson;David Y.Y Yun.

Journal of Algorithms **(1980)**

533 Citations

Two Fast Algorithms for Sparse Matrices: Multiplication and Permuted Transposition

Fred G. Gustavson.

ACM Transactions on Mathematical Software **(1978)**

409 Citations

The Sparse Tableau Approach to Network Analysis and Design

G. Hachtel;R. Brayton;F. Gustavson.

IEEE Transactions on Circuit Theory **(1971)**

404 Citations

FLAME: Formal Linear Algebra Methods Environment

John A. Gunnels;Fred G. Gustavson;Greg M. Henry;Robert A. van de Geijn.

ACM Transactions on Mathematical Software **(2001)**

354 Citations

Implementing Linear Algebra Algorithms for Dense Matrices on a Vector Pipeline Machine

J. J. Dongarra;F. G. Gustavson;A. Karp.

Siam Review **(1984)**

330 Citations

Recursion leads to automatic variable blocking for dense linear-algebra algorithms

F. G. Gustavson.

Ibm Journal of Research and Development **(1997)**

328 Citations

Recursive Blocked Algorithms and Hybrid Data Structures for Dense Matrix Library Software

Erik Elmroth;Fred G. Gustavson;Isak Jonsson;Bo Kågström.

Siam Review **(2004)**

255 Citations

Method and system for dynamically reconfiguring a register file in a vector processor

Ramesh C. Agarwal;Randall D. Groves;Fred G. Gustavson;Mark A. Johnson.

**(1994)**

223 Citations

A three-dimensional approach to parallel matrix multiplication

R. C. Agarwal;S. M. Balle;F. G. Gustavson;M. Joshi.

Ibm Journal of Research and Development **(1995)**

179 Citations

Method and system in a data processing system for loading and storing vectors in a plurality of modes

Ramesh Chandra Agarwal;Randall Dean Groves;Fred G. Gustavson;Mark A. Johnson.

**(1995)**

167 Citations

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