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Automatically exploring computer system design spaces

Published:19 July 2022Publication History

ABSTRACT

While much research has focused on using search to optimize software, it is possible to use these same approaches to optimize other parts of the computer system. With decreased costs in silicon customization, and the return of centralized systems carrying out specialized tasks, the time is right to begin thinking about tools to optimize systems for the needs of specific software targets. In the approach outlined, the standard Genetic Improvement process is flipped with source code considered static and the remainder of the computer system altered to the needs of the software. The project proposed is preliminary research into incorporating grammar-based GP with an advanced computer architecture simulator to automatically design computer systems. I argue this approach has the potential to significantly improve the design of computer systems while reducing manual effort.

References

  1. [n.d.]. SiFive Core Designer. https://www.sifive.com/core-designer. Accessed: 2022-04-05.Google ScholarGoogle Scholar
  2. Jason Lowe-Power et al. 2020. The gem5 Simulator: Version 20.0+. arXiv:arXiv:2007.03152Google ScholarGoogle Scholar
  3. Robert I McKay, Nguyen Xuan Hoai, Peter Alexander Whigham, Yin Shan, and Michael O'neill. 2010. Grammar-based genetic programming: a survey. Genetic Programming and Evolvable Machines 11, 3 (2010), 365--396. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Justyna Petke, Saemundur O Haraldsson, Mark Harman, William B Langdon, David R White, and John R Woodward. 2017. Genetic improvement of software: a comprehensive survey. IEEE Transactions on Evolutionary Computation 22, 3 (2017), 415--432. Google ScholarGoogle ScholarCross RefCross Ref
  5. Adrian Thompson. 2012. Hardware Evolution: Automatic design of electronic circuits in reconfigurable hardware by artificial evolution. Springer Science & Business Media.Google ScholarGoogle Scholar

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      • Published in

        cover image ACM Conferences
        GECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference Companion
        July 2022
        2395 pages
        ISBN:9781450392686
        DOI:10.1145/3520304

        Copyright © 2022 Owner/Author

        This work is licensed under a Creative Commons Attribution International 4.0 License.

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        Association for Computing Machinery

        New York, NY, United States

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        • Published: 19 July 2022

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