An Object Oriented Framework for an Associative Model of Parallel Computation

Department of Computer Science
  1. Open Access Kent State
  2. Kenneth E. Batcher Collection: Papers from the Parallel and Associative Computing Laboratory
  3. An Object Oriented Framework for an Associative Model of Parallel Computation
Author(s)
Abstract

An object oriented description and framework of the Multiple ASsociative Computing (MASC) model of parallel computation is presented. This description identifies MASC objects and specifies various object and inter-object relationships, dependencies, and behaviors. This was achieved by describing various views of the MASC model by using many of the UML structural and behavioral diagrams. This object oriented framework has been highly useful in designing an implementation of a runtime environment for the MASC model. Also the object oriented framework has been highly effective for further parallel modeling techniques, comparisons to other parallel models, MASC parallel system software research, and MASC algorithm development.
Format
Article
Identifier(s)
10.1109/IPDPS.2003.1213309
Publication Date
2003
Publication Title
Proceedings International Parallel and Distributed Processing Symposium
Publisher
IEEE
First Page
166
Last Page
172
Keywords
Subject
Rights
http://rightsstatements.org/vocab/InC/1.0/
Community
Department of Computer Science
Comments

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Scherger, M., Potter, J., & Baker, J. (2003). An Object Oriented Framework for an Associative Model of Parallel Computation (1–). Proceedings International Parallel and Distributed Processing Symposium. https://doi.org/10.1109/IPDPS.2003.1213309
Scherger, Michael, Jerry Potter, and Johnnie Baker. 2003. “An Object Oriented Framework for an Associative Model of Parallel Computation”. Proceedings International Parallel and Distributed Processing Symposium. https://doi.org/10.1109/IPDPS.2003.1213309.
Scherger, Michael, et al. An Object Oriented Framework for an Associative Model of Parallel Computation. Proceedings International Parallel and Distributed Processing Symposium, 2003, https://doi.org/10.1109/IPDPS.2003.1213309.