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Deep Parameter Tuning of Concurrent Divide and Conquer Algorithms in Akka

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Applications of Evolutionary Computation (EvoApplications 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10200))

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Abstract

Akka is a widely-used high-performance and distributed computing toolkit for fine-grained concurrency, written in Scala for the Java Virtual Machine. Although Akka elegantly simplifies the process of building complex parallel software, many crucial decisions that affect system performance are deferred to the user. Employing the method of Deep Parameter Tuning to extract embedded ‘magic numbers’ from source code, we use the CMA-ES evolutionary computation algorithm to optimise the concurrent implementation of three widely-used divide-and-conquer algorithms within the Akka toolkit: Quicksort, Strassen’s matrix multiplication, and the Fast Fourier Transform.

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Notes

  1. 1.

    Strictly, a monad.

  2. 2.

    http://doc.akka.io/docs/akka/current/scala/dispatchers.html.

  3. 3.

    https://commons.apache.org/proper/commons-math/javadocs/api-3.6.1/index.html.

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Authors and Affiliations

  1. CREST, University College London, Malet Place, London, WC1E 6BT, UK

    David R. White & Leonid Joffe

  2. Computer Science, University of York, Deramore Lane, York, YO10 5GH, UK

    Edward Bowles & Jerry Swan

Authors
  1. David R. White
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  2. Leonid Joffe
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  3. Edward Bowles
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  4. Jerry Swan
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Corresponding author

Correspondence to Jerry Swan .

Editor information

Editors and Affiliations

  1. Politecnico di Torino, Turin, Italy

    Giovanni Squillero

  2. Edinburgh Napier University, Edinburgh, United Kingdom

    Kevin Sim

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White, D.R., Joffe, L., Bowles, E., Swan, J. (2017). Deep Parameter Tuning of Concurrent Divide and Conquer Algorithms in Akka. In: Squillero, G., Sim, K. (eds) Applications of Evolutionary Computation. EvoApplications 2017. Lecture Notes in Computer Science(), vol 10200. Springer, Cham. https://doi.org/10.1007/978-3-319-55792-2_3

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  • DOI: https://doi.org/10.1007/978-3-319-55792-2_3

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