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Genetic Improvement of Data for Maths Functions

Genetic Improvement of Data for Maths Functions We use continuous optimisation and manual code changes to evolve up to 1024 Newton-Raphson numerical values embedded in an open source GNU C library glibc square root sqrt to implement a double precision cube root routine cbrt, binary logarithm log2 and reciprocal square root function for C in seconds. The GI inverted square root x-1/2 is far more accurate than Quake’s InvSqrt, Quare root. GI shows potential for automatically creating mobile or low resource mote smart dust bespoke custom mathematical libraries with new functionality. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Evolutionary Learning and Optimization Association for Computing Machinery

Genetic Improvement of Data for Maths Functions

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Publisher
Association for Computing Machinery
Copyright
Copyright © 2021 Copyright held by the owner/author(s). Publication rights licensed to ACM.
ISSN
2688-299X
eISSN
2688-3007
DOI
10.1145/3461016
Publisher site
See Article on Publisher Site

Abstract

We use continuous optimisation and manual code changes to evolve up to 1024 Newton-Raphson numerical values embedded in an open source GNU C library glibc square root sqrt to implement a double precision cube root routine cbrt, binary logarithm log2 and reciprocal square root function for C in seconds. The GI inverted square root x-1/2 is far more accurate than Quake’s InvSqrt, Quare root. GI shows potential for automatically creating mobile or low resource mote smart dust bespoke custom mathematical libraries with new functionality.

Journal

ACM Transactions on Evolutionary Learning and OptimizationAssociation for Computing Machinery

Published: Jul 29, 2021

Keywords: Evolutionary computing

References