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Tim Harris 0002

dblp:149/2458 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1989
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1

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
Parallel and multicore computing · 77% High-performance computing · 23%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Parallel and multicore computing
data-parallel programming		 0.011989
Matrix multiplication on the connection machine · SC 1989
High-performance computing › numerical linear algebra
matrix multiplication		 0.011989
Matrix multiplication on the connection machine · SC 1989
Parallel and multicore computing
parallel computing		 0.011989
Matrix multiplication on the connection machine · SC 1989
Parallel and multicore computing › parallel algorithms › parallel algorithm design
systolic algorithms		 0.011989
Matrix multiplication on the connection machine · SC 1989
Parallel and multicore computing › array processor
connection machine		 0.011989
Matrix multiplication on the connection machine · SC 1989

Methods — techniques the papers use, named apart from their topics

systolic algorithm · 0.0matrix-vector multiplication primitive · 0.0
YearPublicationVenuePosition
1989 Matrix multiplication on the connection machine
abstract
A data parallel implementation of the multiplication of matrices of arbitrary shapes and sizes is presented. A systolic algorithm based on a rectangular processor layout is used by the implementation. All processors contain submatrices of the same size for a given operand. Matrix-vector multiplication is used as a primitive for local matrix-matrix multiplication in the Connection Machine system CM-2 implementation. The peak performance of the local matrix-matrix multiplication is in excess of 20 Gflops s-1. The overall algorithm including all required data motion has a peak performance of 5.8 Gflops s-1.
S. Lennart Johnsson, Tim Harris 0002, Kapil K. Mathur
 SC2