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Parallel asynchronous algorithms for discrete data
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Source Journal of the ACM (JACM) archive
Volume 37 ,  Issue 3  (July 1990) table of contents
Pages: 588 - 606  
Year of Publication: 1990
ISSN:0004-5411
Authors
Aydin Üresin  Univ. of Southern California, Los Angeles
Michel Dubois  Univ. of Southern California, Los Angeles
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 6,   Downloads (12 Months): 42,   Citation Count: 7
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ABSTRACT

Many problems in the area of symbolic computing can be solved by iterative algorithms. Implementations of these algorithms on multiprocessors can be synchronous or asynchronous. Asynchronous implementations are potentially more efficient because synchronization is a major source of performance degradation in most multiprocessor systems. In this paper, sufficient conditions for the convergence of asynchronous iterations to desired solutions are given. The main sufficient condition is shown to be also necessary for the case of finite data domains. The results are applied to prove the convergence of three asynchronous algorithms for the all-pairs shortest path problem, the consistent labeling problem, and a neural net model.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Aydin Üresin: colleagues
Michel Dubois: colleagues