Evolution of Complex Combinational Logic Circuits Using Grammatical Evolution with SystemVerilog

Michael Kwaku Tetteh, Douglas Mota Dias, Conor Ryan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Scalability problems have hindered the progress of Evolvable Hardware in tackling complex circuits. The two key issues are the amount of testing (for example, a 64-bit × 64-bit add-shift multiplier problem has 2 64 + 64 test cases) and low level that hardware works at: a circuit to implement 64-bit × 64-bit add-shift multiplier would require approximately 33,234 gates when synthesized using the powerful Yosys Open SYnthesis Suite tool. We use Grammatical Evolution and SystemVerilog, a Hardware Description Language (HDL), to evolve fully functional parameterized adder, multiplier and selective parity circuits with default input bit-width sizes of 64-bit + 64-bit, 64-bit × 64-bit and 128-bit respectively. These are substantially larger than the current state of the art for evolutionary approaches, specifically, 6.4 × (adder), 10.7 × (multiplier), and 6.7 × (parity). We are able to scale so dramatically because our use of an HDL permits us to operate at a far higher level of abstraction than most other approaches. This has the additional benefit that no further evolutionary experiments are needed to design different input bit-width sizes of the same circuit as is the case for existing EHW approaches. Thus, one can evolve once and reuse multiple times, simply by specifying the newly desired input/output bit-width sizes during module instantiation. For example, 32-bit × 32-bit and 256-bit × 256-bit multipliers can be instantiated from an evolved parameterized multiplier. We also adopt a method for reducing testing from Digital Circuit Design known as corner case testing, well-known technique heavily relied upon by circuit designers to avoid time-consuming exhaustive testing; we demonstrate a simple way to identify and use corner cases for evolutionary testing and show that it enables the generation of massively complex circuits with a huge number of inputs. We obtain successful results (ranging from 72% to 100%) on each benchmark and all three problems were tackled without resorting to the use of any standard decomposition methods due to our ability to use high-level programming constructs and operators available in SystemVerilog.

Original languageEnglish
Title of host publicationGenetic Programming - 24th European Conference, EuroGP 2021, Held as Part of EvoStar 2021, Proceedings
EditorsTing Hu, Nuno Lourenço, Eric Medvet
PublisherSpringer Science and Business Media Deutschland GmbH
Pages146-161
Number of pages16
ISBN (Print)9783030728113
DOIs
Publication statusPublished - 2021
Event24th European Conference on Genetic Programming, EuroGP 2021 - Virtual, Online
Duration: 7 Apr 20219 Apr 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12691 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference24th European Conference on Genetic Programming, EuroGP 2021
CityVirtual, Online
Period7/04/219/04/21

Keywords

  • Digital circuit design
  • Evolvable Hardware
  • Grammatical Evolution
  • Hardware Description Languages (HDLs)
  • SystemVerilog
  • Verilog

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