10-14 July 2016
Africa/Johannesburg timezone
Paper Submission is Open!! Registration for CCP2016 Conference will be open at the registration desk @ St. George's Hotel reception area on Sunday 10 July / Welcome Dinner at 18:30 SAST.

Efficient parallelization of scientific computer codes: Two case studies using the PGAS programming model

14 Jul 2016, 09:30
20m

Speaker

Ms Martina Prugger (University of Innsbruck)

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Efficient implementation of numerical methods is one of the most important aspects of computational physics. Especially simulations that are computationally expensive or run for a long time benefit from the use of modern HPC systems. To fully exploit the potential of these systems, parallelization of the code is necessary. Developing a parallel code, however, is usually a difficult task for the developer.
The partitioned global address space (PGAS) approach is a programming model that promises to simplify the process of parallel programming as compared to the widely used MPI model.
In this study we have used unified parallel C (UPC), an extension to the C programming language that implements the PGAS paradigm, to evaluate the ease of development as well as the efficiency of this programming model for two different case studies representative for a wide variety of problems commonly found in computational physics applications:
On the one hand, we implemented a Godunov solver for the two dimensional Euler equations of gas dynamics. This case is a compute bound problem due to the Riemann solver needed to compute the flux at the cell interfaces but employs a fairly straight forward data structure.
On the other hand, we have investigated a sparse matrix vector multiplication (SPMV) problem resulting from solving the diffusion equation using cell-centered finite volumes. This problem uses a highly irregular mesh in order to allow for the simulation of complicated structures (e.g., the human heart). This case is memory bound and uses a non-trivial data structure.

Primary author

Ms Martina Prugger (University of Innsbruck)

Co-authors

Prof. Alexander Ostermann (University of Innsbruck) Dr Johannes Langguth (SIMULA Research Laboratory) Mr Jérémie Lagravière (SIMULA Research Laboratory) Dr Lukas Einkemmer (University of Innsbruck) Prof. Xing Cai (SIMULA Research Laboratory)

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