Adaptive GA: An Essential Ingredient in High-Level Synthesis


Choong, Florence Chiao Mei and Somnuk, Phon-Amnuaisuk and Alias, Mohamad Yusoff and Pang, Wai Leong (2008) Adaptive GA: An Essential Ingredient in High-Level Synthesis. In: IEEE Congress on Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Xplore, pp. 3837-3844. ISBN 978-1-4244-1823-7

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High-level synthesis, a crucial step in VLSI and System on Chip (SoC) design, is the process of transforming an algorithmic or behavioral description into a structural specification of the architecture realizing the behavior. In the past, researchers have attempted to apply GAs to the HLS domain. This is motivated by the fact that the search space for HLS is large and GAs are known to work well on such problems. However, the process of GA is controlled by several parameters, e.g. crossover rate and mutation rate that largely determine the success and efficiency of GA in solving a specific problem. Unfortunately, these parameters interact with each other in a complicated way and determining which parameter set is best to use for a specific problem can be a complex task requiring much trial and error. This inherent drawback is overcome in this paper where it presents two adaptive GA approaches to HLS, the adaptive GA operator probability (AGAOP) and adaptive operator selection (AOS) and compares the performance to the standard GA (SGA) on eight digital logic benchmarks with varying complexity. The AGAOP and AOS are shown to be far more robust than the SGA, providing fast and reliable convergence across a broad range of parameter settings. The results show considerable promise for adaptive approaches to HLS domain and opens up a path for future work in this area.

Item Type: Book Section
Subjects: T Technology > T Technology (General)
Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions: Faculty of Engineering (FOE)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 21 Sep 2011 07:34
Last Modified: 24 Jul 2014 04:26


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