Genetic improvement of data for maths functions

William B. Langdon, Oliver Krauss

Publikation: Beitrag in Buch/Bericht/TagungsbandKonferenzbeitragBegutachtung

Abstract

Genetic Improvement (GI) can be used to give better quality software and to create new functionality. We show that GI can evolve the PowerPC open source GNU C runtime library square root function into cube root, binary logarithm log2 and reciprocal square root. The GI cbrt is competitive in run-time performance and our inverted square root x-1/2 is far more accurate than the approximation used in the Quake video game. We use CMA-ES to adapt constants in a Newton-Raphson table, originally from glibc's sqrt, for other double precision mathematics functions. Such automatically customised math libraries might be used for mobile or low resource, IoT, mote, smart dust, bespoke cyber-physical systems. Evolutionary Computing (EC) can be used to not only adapt source code but also data, such as numerical constants, and could enable a new way to conduct software data maintenance. This is an exciting opportunity for the GECCO and optimisation communities.

OriginalspracheEnglisch
TitelGECCO 2021 Companion - Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion
Herausgeber (Verlag)Association for Computing Machinery, Inc
Seiten31-32
Seitenumfang2
ISBN (elektronisch)9781450383516
DOIs
PublikationsstatusVeröffentlicht - 7 Juli 2021
Veranstaltung2021 Genetic and Evolutionary Computation Conference, GECCO 2021 - Virtual, Online, Frankreich
Dauer: 10 Juli 202114 Juli 2021

Publikationsreihe

NameGECCO 2021 Companion - Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion

Konferenz

Konferenz2021 Genetic and Evolutionary Computation Conference, GECCO 2021
Land/GebietFrankreich
OrtVirtual, Online
Zeitraum10.07.202114.07.2021

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