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

Andrew White

Research output: Contribution to conferencePaperpeer-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
Number of pages7
Publication statusPublished (VoR) - 1997
EventIEE Colloquium on Mixed-Signal AHDL/VHDL Modelling and Synthesis - IET London: Savoy Place, London, United Kingdom
Duration: 19 Nov 199719 Nov 1997
Conference number: 1997/331;jsessionid=1k5krkmgua0lb.x-iet-live-01


ConferenceIEE Colloquium on Mixed-Signal AHDL/VHDL Modelling and Synthesis
Country/TerritoryUnited Kingdom
Internet address


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