Study of GPU Acceleration in Genetic Algorithms for Quantum Circuit Synthesis

Martin Lukac, Georgiy Krylov

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In this work we present a comparative study of several GPU accelerated elements of a Genetic Algorithm (GA) for the synthesis of quantum circuits on the level of Electro-Magnetic (EM) pulses. The novelty in our approach is in the implementation: a) a completely GPU accelerated quantum simulator, b) GPU accelerated genetic operators and fitness evaluation and finally c) a set of GPU implemented optimizations for GPU accelerated evolutionary search optimization for the synthesis of quantum circuits. The reason for using EM pulses model for synthesis is the observation that this model requires the largest amount of elementary rotations to implement quantumlogic gates and thus provides a good measure to evaluate the efficiency of the acceleration by the GPU processor. The reason to use a GA is the advantage of pseudo evolutionary search in very large problem space such as the one defined by the Ising model where the EM realized quantum circuits are evolved. As a result of the several GPU optimizations several new circuits implementations are presented and their cost is compared to thecurrently known Ising model implementations.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE 47th International Symposium on Multiple-Valued Logic, ISMVL 2017
PublisherIEEE Computer Society
Pages213-218
Number of pages6
ISBN (Electronic)9781509054954
DOIs
Publication statusPublished - Jun 30 2017
Event47th IEEE International Symposium on Multiple-Valued Logic, ISMVL 2017 - Novi Sad, Serbia
Duration: May 22 2017May 24 2017

Conference

Conference47th IEEE International Symposium on Multiple-Valued Logic, ISMVL 2017
CountrySerbia
CityNovi Sad
Period5/22/175/24/17

Fingerprint

Quantum Circuits
Genetic algorithms
Genetic Algorithm
Synthesis
Ising Model
Optimization
Networks (circuits)
Genetic Operators
Electromagnetic pulse
Ising model
Fitness
Comparative Study
Simulator
Evaluate
Evaluation
Costs
Model
Graphics processing unit
Simulators

Keywords

  • Evolutionary computation
  • GPU
  • Optimization
  • Quantum Circuits

ASJC Scopus subject areas

  • Computer Science(all)
  • Mathematics(all)

Cite this

Lukac, M., & Krylov, G. (2017). Study of GPU Acceleration in Genetic Algorithms for Quantum Circuit Synthesis. In Proceedings - 2017 IEEE 47th International Symposium on Multiple-Valued Logic, ISMVL 2017 (pp. 213-218). [7964993] IEEE Computer Society. https://doi.org/10.1109/ISMVL.2017.24

Study of GPU Acceleration in Genetic Algorithms for Quantum Circuit Synthesis. / Lukac, Martin; Krylov, Georgiy.

Proceedings - 2017 IEEE 47th International Symposium on Multiple-Valued Logic, ISMVL 2017. IEEE Computer Society, 2017. p. 213-218 7964993.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Lukac, M & Krylov, G 2017, Study of GPU Acceleration in Genetic Algorithms for Quantum Circuit Synthesis. in Proceedings - 2017 IEEE 47th International Symposium on Multiple-Valued Logic, ISMVL 2017., 7964993, IEEE Computer Society, pp. 213-218, 47th IEEE International Symposium on Multiple-Valued Logic, ISMVL 2017, Novi Sad, Serbia, 5/22/17. https://doi.org/10.1109/ISMVL.2017.24
Lukac M, Krylov G. Study of GPU Acceleration in Genetic Algorithms for Quantum Circuit Synthesis. In Proceedings - 2017 IEEE 47th International Symposium on Multiple-Valued Logic, ISMVL 2017. IEEE Computer Society. 2017. p. 213-218. 7964993 https://doi.org/10.1109/ISMVL.2017.24
Lukac, Martin ; Krylov, Georgiy. / Study of GPU Acceleration in Genetic Algorithms for Quantum Circuit Synthesis. Proceedings - 2017 IEEE 47th International Symposium on Multiple-Valued Logic, ISMVL 2017. IEEE Computer Society, 2017. pp. 213-218
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