Unlocking approximation for in-memory computing with Cartesian genetic programming and computer algebra for arithmetic circuits

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@Article{DBLP:journals/it/FrohlichD22,

• author = "Saman Froehlich and Rolf Drechsler",
• title = "Unlocking approximation for in-memory computing with Cartesian genetic programming and computer algebra for arithmetic circuits",
• journal = "it - Information Technology",
• volume = "64",
• number = "3",
• pages = "99--107",
• year = "2022",
• keywords = "genetic algorithms, genetic programming, Cartesian genetic programming, CGP, Approximate Computing, In-Memory Computing, ReRAM, RRAM, Symbolic Computer Algebra, SCA, PLiM, EA",
• timestamp = "Thu, 10 Nov 2022 00:00:00 +0100",
• biburl = "https://dblp.org/rec/journals/it/FrohlichD22.bib",
• bibsource = "dblp computer science bibliography, https://dblp.org",
• URL = "https://doi.org/10.1515/itit-2021-0042",
• DOI = "doi:10.1515/itit-2021-0042",
• size = "9 pages",
• abstract = "... approximate computing techniques to in-memory computing. We extend existing compilation techniques for the Programmable Logic in Memory (PLiM) computer architecture, by adapting state-of-the-art approximate computing techniques for arithmetic circuits. We use Cartesian Genetic Programming for the generation of approximate circuits and evaluate them using a Symbolic Computer Algebra-based technique with respect to error-metrics. In our experiments, we show that we can outperform state-of-the-art handcrafted approximate adder designs.",

}

Genetic Programming entries for Saman Froehlich Rolf Drechsler

Citations