The main purpose of the present paper is the study of computational aspects, ## Ž . and primarily the convergence rate, of genetic algorithms GAs . Despite the fact that such algorithms are widely used in practice, little is known so far about their theoretical properties, and in particular about
Effects of Asynchronism on the Convergence Rate of Iterative Algorithms
✍ Scribed by Aydin Üresin; Michel Dubois
- Publisher
- Elsevier Science
- Year
- 1996
- Tongue
- English
- Weight
- 392 KB
- Volume
- 34
- Category
- Article
- ISSN
- 0743-7315
No coin nor oath required. For personal study only.
✦ Synopsis
In multiprocessor systems, iterative algorithms can be implemented synchronously or asynchronously. Unfortunately, few guidelines exist to make a choice. In this paper, we compare the execution times of an asynchronous iterative algorithm and of its synchronous counterpart. Synchronization overhead and communication times are neglected in order to focus on the effect of asynchronism on the convergence rate. Under some assumptions, we derive an analytical model. In this model, Q tasks with identical and independently distributed execution time distributions execute on P processors. We show the effects of execution time fluctuations, of the number of processors and tasks, of the scheduling policy and of the amount of coupling among iterate components. The models show that the asynchronous iteration may be up to twice as slow as the synchronous one. This worst case is achieved when the processing time fluctuations are very small, and the coupling among components is strong.
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