research-article

Performance improvements of evolutionary algorithms in perl 6

Authors:

Juan-Julián Merelo-Guervós,

José-Mario García-ValdezAuthors Info & Claims

GECCO '18: Proceedings of the Genetic and Evolutionary Computation Conference Companion

Pages 1371 - 1378

https://doi.org/10.1145/3205651.3208273

Published: 06 July 2018 Publication History

Abstract

Perl 6 is a recently released language that belongs to the Perl family but was actually designed from scratch, not as a refactoring of the Perl 5 codebase. Through its two-year-old (released) history, it has increased performance by several orders of magnitude, arriving recently to the point where it can be safely used in production. In this paper, we are going to compare the historical and current performance of Perl 6 in a single problem, OneMax, to those of other interpreted languages; besides, we will also use implicit concurrency and see what kind of performance and scaling can we expect from it.

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Cited By

Merelo-Guervós JGarcía-Valdez MCastillo P(2024)Green Evolutionary Algorithms and JavaScript: A Study on Different Software and Hardware ArchitecturesSoftware Technologies10.1007/978-3-031-61753-9_1(1-18)Online publication date: 24-May-2024
https://doi.org/10.1007/978-3-031-61753-9_1
Guervós JGarcía-Valdez MRojas-Galeano SCoello Coello C(2020)Implementation matters, also in concurrent evolutionary algorithmsProceedings of the 2020 Genetic and Evolutionary Computation Conference Companion10.1145/3377929.3398120(1591-1598)Online publication date: 8-Jul-2020
https://dl.acm.org/doi/10.1145/3377929.3398120

Index Terms

Performance improvements of evolutionary algorithms in perl 6
1. Computing methodologies
  1. Distributed computing methodologies
    1. Distributed algorithms
2. Theory of computation
  1. Design and analysis of algorithms
    1. Mathematical optimization
      1. Discrete optimization
        Optimization with randomized search heuristics
        Evolutionary algorithms

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cover image ACM Conferences

GECCO '18: Proceedings of the Genetic and Evolutionary Computation Conference Companion

July 2018

1968 pages

ISBN:9781450357647

DOI:10.1145/3205651

Editor:
Hernan Aguirre
Shinshu University
,
General Chair:
Keiki Takadama
The University of Electro-Communications

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 July 2018

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Ministerio de Ciencia y Tecnología

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GECCO '18

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SIGEVO

GECCO '18: Genetic and Evolutionary Computation Conference

July 15 - 19, 2018

Kyoto, Japan

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

Merelo-Guervós JGarcía-Valdez MCastillo P(2024)Green Evolutionary Algorithms and JavaScript: A Study on Different Software and Hardware ArchitecturesSoftware Technologies10.1007/978-3-031-61753-9_1(1-18)Online publication date: 24-May-2024
https://doi.org/10.1007/978-3-031-61753-9_1
Guervós JGarcía-Valdez MRojas-Galeano SCoello Coello C(2020)Implementation matters, also in concurrent evolutionary algorithmsProceedings of the 2020 Genetic and Evolutionary Computation Conference Companion10.1145/3377929.3398120(1591-1598)Online publication date: 8-Jul-2020
https://dl.acm.org/doi/10.1145/3377929.3398120

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