Highly Parallel Computation

Highly parallel computing architectures are the only means to achieve the computational rates demanded by advanced scientific problems. A decade of research has demonstrated the feasibility of such machines, and current research focuses on which architectures are best suited for particular classes o...

Full description

Saved in:
Bibliographic Details
Published in:Science (American Association for the Advancement of Science) Vol. 250; no. 4985; pp. 1217 - 1222
Main Authors: Denning, Peter J., Tichy, Walter F.
Format: Journal Article
Language:English
Published: Legacy CDMS American Society for the Advancement of Science 30.11.1990
American Association for the Advancement of Science
The American Association for the Advancement of Science
Subjects:
Algorithms
Architecture
Broadcasting industry
Computer architecture
Computer memory
Computer Operations And Hardware
Computer programming
Computer programming & languages
Computer science education
Computers
Connection machine
Data processing
Electronic data processing
Electronic data processing in research
Equipment and supplies
Machinery
Parallel computing
Parallel processing
Science
Single instruction multiple data computers
ISSN:0036-8075, 1095-9203
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Highly parallel computing architectures are the only means to achieve the computational rates demanded by advanced scientific problems. A decade of research has demonstrated the feasibility of such machines, and current research focuses on which architectures are best suited for particular classes of problems. The architectures designated as MIMD and SIMD have produced the best results to date; neither shows a decisive advantage for most near-homogeneous scientific problems. For scientific problems with many dissimilar parts, more speculative architectures such as neural networks or data flow may be needed.
Bibliography:CDMS
Legacy CDMS
ISSN: 0036-8075
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ObjectType-Article-2
content type line 23
ObjectType-Article-1
ObjectType-Feature-2
ISSN:0036-8075
1095-9203
DOI:10.1126/science.250.4985.1217