Demo Data from SIGIR 2026 / reviewers in the wild / expert
Thomas Turnbull
dblp:41/4605
· DBLP profile ↗
3ranked-venue papers
0as first author
0since 2021 · last 1996
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 3
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
High-performance computing · 91% Performance modeling and evaluation · 9% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
High-performance computing › numerical linear algebra
dense linear algebra |
0.0 | 1 | 1996 | Implementation of Strassen's Algorithm for Matrix Multiplication · SC 1996 |
High-performance computing › numerical linear algebra
matrix multiplication |
0.0 | 1 | 1996 | Implementation of Strassen's Algorithm for Matrix Multiplication · SC 1996 |
High-performance computing › numerical linear algebra
strassen's algorithm |
0.0 | 1 | 1996 | Implementation of Strassen's Algorithm for Matrix Multiplication · SC 1996 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1996 | Implementation of Strassen's Algorithm for Matrix MultiplicationabstractIn this paper we report on the development of an efficient and portable implementation of Strassen's matrix multiplication algorithm for matrices of arbitrary size. Our technique for defining the criterion which stops the recursions is more detailed than those generally used, thus allowing enhanced performance for a larger set of input sizes. In addition, we deal with odd matrix dimensions using a method whose usefulness had previously been in question and had not so far been demonstrated. Our memory requirements have also been reduced, in certain cases by 40 to more than 70 percent over other similar implementations. We measure performance of our code on the IBM RS/6000, CRAY YMP C90, and CRAY T3D single processor, and offer comparisons to other codes. Finally, we demonstrate the usefulness of our implementation by using it to perform the matrix multiplications in a large application code. Steven Huss-Lederman, Elaine M. Jacobson, J. R. Johnson, Anna Tsao, Thomas Turnbull |
SC | 5 |
| 1991 | FFTs and three-dimensional Poisson solvers for hypercubes
Roland A. Sweet, William L. Briggs, Suely Oliveira, Jules L. Porsche, Thomas Turnbull |
Parallel Comput. | 5 |
| 1988 | Fast Poisson solvers for MIMD computers
William L. Briggs, Thomas Turnbull |
Parallel Comput. | 2 |