Paper Info
Title
What Computer Architecture Can Learn From Computational Intelligence - And Vice Versa
Abstract
This paper considers whether the seemingly disparate fields of Computational Intelligence (CI) and computer architecture can profit from each others' principles, results and experience. In the process, we identify important common issues, such as parallelism, distribution of data and control, granularity and regularity. We present two novel computer architectures which have profited from principles found in CI, and identify two constraints on CI to eliminate the hidden influence of the von Neumann model of computation.
Year
DOI
Venue
1997
10.1109/EURMIC.1997.617402
23RD EUROMICRO CONFERENCE - NEW FRONTIERS OF INFORMATION TECHNOLOGY, PROCEEDINGS
Keywords
Field
DocType
neuro-computing,parallelizing compilers.,parallel and distributed systems,memory systems and management,multithreaded architecture,computer architecture,profitability,artificial intelligence,neural nets,computational intelligence
Cellular architecture,Computer architecture,Applications architecture,Dataflow architecture,Computational intelligence,Computer science,Theoretical computer science,Granularity,Artificial neural network,Von Neumann architecture,Computation
Conference
ISSN
Citations 
PageRank 
1089-6503
0
0.34
References 
Authors
3
3
Name
Order
Citations
PageRank
Ronald Moore1417.60
Bernd Klauer25014.36
Klaus Waldschmidt312230.92