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GAME-HDL: Implementation of evolutionary algorithms using hardware description languages. (English) Zbl 1033.68621

Cagnoni, Stefano (ed.) et al., Applications of evolutionary computing. EvoWorkshops 2003: EvoBIO, EvoCOP, EvoIASP, EvoMUSART, EvoROB, and EvoSTIM, Essex, UK, April 14–16, 2003. Proceedings. Berlin: Springer (ISBN 3-540-00976-0/pbk). Lect. Notes Comput. Sci. 2611, 378-387 (2003).
Summary: Evolutionary Algorithms (EAs) have been proposed as a very powerful heuristic optimization technique to solve complex problems. Many case studies have shown that they work very efficient on a large set of problems, but in general the high qualities can only be obtained by high run time costs. In the past several approaches based on parallel implementations have been studied to speed up EAs. In this paper we present a technique for the implementation of EAs in hardware based on a the concept of reusable modules. These modules are described in a Hardware Description Language (HDL). The resulting “hardware EA” can be directly synthesized and mapped to Application Specific Integrated Circuits (ASICs) or Field Programmable Gate Arrays (FPGAs). This approach finds direct application in signal processing, where hardware implementations are often needed to meet the run time requirements of a real-time system. In our prototype implementation we used VHDL and synthesized an EA for solving the OneMax problem. Simulation results show the feasibility of the approach. Due to the use of a standard HDL, the components can be reused in the form of a library.
For the entire collection see [Zbl 1017.68610].

MSC:

68T20 Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.)
68T05 Learning and adaptive systems in artificial intelligence

Software:

GAME-HDL
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