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Accueil > Publications > Thèses > Archives Thèses > Thèses 2013 - 2014


Contributions to parallel stochastic simulation : Application of good software engineering practices to the distribution of pseudorandom streams in hybrid Monte-Carlo simulations

Vendredi 11 octobre 2013 - 10h 00 - Amphi 1 du pôle commun Polytech/ISIMA

The race to computing power increases every day in the simulation community. A few years ago, scientists have started to harness the computing power of Graphics Processing Units (GPUs) to parallelize their simulations. As with any parallel architecture, not only the simulation model implementation has to be ported to the new parallel platform, but all the tools must be reimplemented as well. In the particular case of stochastic simulations, one of the major element of the implementation is the pseudorandom numbers source. Employing pseudorandom numbers in parallel applications is not a straightforward task, and it has to be done with caution in order not to introduce biases in the results of the simulation. This problematic has been studied since parallel architectures are available and is called pseudorandom stream distribution. While the literature is full of solutions to handle pseudorandom stream distribution on CPU-based parallel platforms, the young GPU programming community cannot display the same experience yet. In this thesis, we study how to correctly distribute pseudorandom streams on GPU. From the existing solutions, we identified a need for good software engineering solutions, coupled to sound theoretical choices in the implementation. We propose a set of guidelines to follow when a PRNG has to be ported to GPU, and put these advice into practice in a software library called ShoveRand. This library is used in a stochastic Polymer Folding model that we have implemented in C++/CUDA. Pseudorandom streams distribution on manycore architectures is also one of our concerns. It resulted in a contribution named TaskLocalRandom, which targets parallel Java applications using pseudorandom numbers and task frameworks. Eventually, we share a reflection on the methods to choose the right parallel platform for a given application. In this way, we propose to automatically build prototypes of the parallel application running on a wide set of architectures. This approach relies on existing software engineering tools from the Java and Scala community, most of them generating OpenCL source code from a high-level abstraction layer.

Jury :
Pr. Michael MASCAGNI, Florida State Univ. – USA - Reviewers
Pr. Stéphane VIALLE, Supélec, campus de Metz. - Reviewers
Pr. David R.C. HILL, Blaise Pascal Univ. - Supervisor
Pr. Alain QUILLIOT, Blaise Pascal Univ. - Chairman
Pr. Pierre L’ECUYER, Montreal Univ. – Canada - Examiners
Pr. Makoto MATSUMOTO, Hiroshima Univ. – Japan - Examiners
Dr. Bruno BACHELET, Blaise Pascal Univ. - Examiners
Dr. Claude MAZEL, Blaise Pascal Univ. - Examiners