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Physics simulations are known to be great resources exhausters (CPU, memory). Hardware acceleration can help reduce the need for CPU time and increase the available memory bandwidth. In this paper, we present the performance gain when running a memory-bound muon Monte Carlo simulation on an Intel Xeon Phi and an Intel Xeon CPU. We show how to increase performance on the Xeon Phi without modifying...
High Performance Computing systems expect applications to leverage the most of their processing power. This need is even more present for applications such as Monte Carlo simulations that require noteworthy CPU time and memory footprint. Optimizing applications is one approach to reduce the consumption of these resources. Before optimizing, it is mandatory to profile the application in order to pinpoint...
Most Monte Carlo simulations can be parallelized, or at least easily distributed. However, the parallelization of such programs is not mainstream. In this paper, we propose good practices to distribute a Monte Carlo simulation for computed tomography. We apply this to large edifices (such as volcanoes or pyramids) and give a particular focus on performances. The work included first the optimization...
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