Automated generation of system-level AHDL architectures using a genetic algorithm

Andy White, Philip Hallam, Richard Binns

Research output: Contribution to journalArticlepeer-review


This paper presents a methodology for the automated generation of optimised system-level AHDL architectures from AHDL system-level specifications using a GA. The synthesis process begins with a set of randomly generated system-level topologies and model parameters. Genetic operators, selection, crossover and mutation, are applied to evolve the population of topologies to a population of system-level architectures in which topologies and model parameters meet the required performance specifications. Both topology and model parameters evolve simultaneously. Simulations are performed in the time domain with an AHDL behavioural model library of system-level building blocks. The integration and exploitation of AHDL simulation based design allows for an efficient and flexible system-level synthesis methodology with less dependency on a knowledge-based approach and complex design equations. The methodology has been successfully demonstrated for the design of a DSB-SC-AM demodulation chain, for which an optimised system-level AHDL architecture has been produced fulfilling the required input AHDL system-level specification.
Original languageEnglish
Pages (from-to)5/1-5/7
JournalIEE Colloquium (Digest)
Issue number331
Publication statusPublished - 1997


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