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Playdoh: A lightweight Python library for distributed computing and optimisation

Cyrille Rossant, Bertrand Fontaine, Dan F.M. Goodman
Laboratoire Psychologie de la Perception, CNRS and Universite Paris Descartes, Paris, France
Journal of Computational Science, 2011

@article{rossant2011playdoh,

   title={Playdoh: a lightweight Python library for distributed computing and optimisation},

   author={Rossant, C. and Fontaine, B. and Goodman, D.F.M.},

   journal={Journal of Computational Science},

   year={2011},

   publisher={Elsevier}

}

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Parallel computing is now an essential paradigm for high performance scientific computing. Most existing hardware and software solutions are expensive or difficult to use. We developed Playdoh, a Python library for distributing computations across the free computing units available in a small network of multicore computers. Playdoh supports independent and loosely coupled parallel problems such as global optimisations, Monte Carlo simulations and numerical integration of partial differential equations. It is designed to be lightweight and easy to use and should be of interest to scientists wanting to turn their lab computers into a small cluster at no cost.
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