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1 ISIMA - Institut Supérieur d-Informatique, de Modélisation et de leurs Applications 2 Clermont Université 3 LIMOS - Laboratoire d-Informatique, de Modélisation et d-optimisation des Systèmes 4 UBP - Université Blaise Pascal - Clermont-Ferrand 2 5 ISC-PIF - Institut des Systèmes Complexes - Paris Ile-de-France

Abstract : At the manycore era, every simulation practitioner can take advantage of the com-puting horsepower delivered by the available high performance computing devices. From multicoreCPUs Central Processing Unit to thousand-thread GPUs Graphics Processing Unit, severalarchitectures are now able to offer great speed-ups to simulations. However, it is often tricky toharness them properly, and even more complicated to implement a few declinations of the samemodel to compare the parallelizations. Thus, simulation practitioners would mostly benefit of asimple way to evaluate the potential benefits of choosing one platform or another to parallelizetheir simulations. In this work, we study the ability of the Scala programming language to fulfillthis need. We compare the features of two frameworks in this study: Scala Parallel Collections andScalaCL. Both of them provide facilities to set up a data-parallelism approach on Scala collections.The capabilities of the two frameworks are benchmarked with three simulation models as well asa large set of parallel architectures. According to our results, these two Scala frameworks shouldbe considered by the simulation community to quickly prototype parallel simulations, and choosethe target platform on which investing in an optimized development will be rewarding.

Keywords : Manycore Parallelization of Simulation Threads OpenCL Scala Automatic Parallelization GPU





Author: Jonathan Passerat-Palmbach - Romain Reuillon - Claude Mazel - David Hill -

Source: https://hal.archives-ouvertes.fr/



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