Unlocking approximation for in-memory computing with Cartesian genetic programming and computer algebra for arithmetic circuits
Created by W.Langdon from
gp-bibliography.bib Revision:1.8414
- @Article{DBLP:journals/it/FrohlichD22,
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author = "Saman Froehlich and Rolf Drechsler",
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title = "Unlocking approximation for in-memory computing with
Cartesian genetic programming and computer algebra for
arithmetic circuits",
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journal = "it - Information Technology",
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volume = "64",
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number = "3",
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pages = "99--107",
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year = "2022",
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keywords = "genetic algorithms, genetic programming, Cartesian
genetic programming, CGP, Approximate Computing,
In-Memory Computing, ReRAM, RRAM, Symbolic Computer
Algebra, SCA, PLiM, EA",
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timestamp = "Thu, 10 Nov 2022 00:00:00 +0100",
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biburl = "
https://dblp.org/rec/journals/it/FrohlichD22.bib",
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bibsource = "dblp computer science bibliography, https://dblp.org",
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URL = "
https://doi.org/10.1515/itit-2021-0042",
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DOI = "
doi:10.1515/itit-2021-0042",
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size = "9 pages",
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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