Speeding up quantum genetic algorithms in matlab through the quack_GPU V1

Oscar Montiel, Roberto Sepúlveda, Yoshio Rubio

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Quantum computing is inspired in quantum mechanical phenomena and uses superposition and entanglement to process data at very high speeds outperforming conventional computers on some tasks. At present, the access for testing algorithms in commercial quantum computers is too expensive for most institutions; hence, it is very important to have alternatives for testing quantum algorithms. In this paper, we present the results obtained when optimizing a two variables multimodal function when it was optimized through the Quack_GPU v1, which is a modification of the original software Quack! We show that it is possible to obtain speedups up to 8.4× using a Graphic Processing Unit (GPU) computer card with thousands of cores, saving hours of processing time. Performance comparative results of the Quack! vs. the Quack_GPU are presented.

Original languageEnglish
Title of host publicationAdvances in Intelligent Systems and Computing
PublisherSpringer Verlag
Pages156-161
Number of pages6
DOIs
StatePublished - 2018
Externally publishedYes

Publication series

NameAdvances in Intelligent Systems and Computing
Volume648
ISSN (Print)2194-5357

Keywords

  • High-performance
  • QGA
  • Quantum genetic algorithm

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