2014SNA + MC 2013 - Joint International Conference on Supercomputing in Nuclear Applications + Monte Carlo
|Number of page(s)||8|
|Section||4. Advanced Parallelism and HPC Strategies: a. Deterministic Methods, Parallelism and HPC|
|Published online||06 June 2014|
Vectorization of a 2D–1D Iterative Algorithm for the 3D Neutron Transport Problem in Prismatic Geometries
EDF R&D, SINETICS department, 1 av. du Général de Gaulle, 92140 Clamart, France
The past few years have been marked by a noticeable increase in the interest in 3D whole-core heterogeneous deterministic neutron transport solvers for reference calculations. Due to the extremely large problem sizes tackled by such solvers, they need to use adapted numerical methods and need to be efficiently implemented to take advantage of the full computing power of modern systems.
As for numerical methods, one possible approach consists in iterating over resolutions of 2D and 1D MOC problems by taking advantage of prismatic geometries. The MICADO solver, developed at EDF R&D, is a parallel implementation of such a method in distributed and shared memory systems. However it is currently unable to use SIMD vectorization to leverage the full computing power of modern CPUs.
In this paper, we describe our first effort to support vectorization in MICADO, typically targeting Intel© SSE CPUs.
Both the 2D and 1D algorithms are vectorized, allowing for high expected speedups for the whole spatial solver. We present benchmark computations, which show nearly optimal speedups for our vectorized implementation on the TAKEDA case.
Key words: Method of Characteristics (MOC) / MICADO / prismatic geometry / SIMD / Intel SSE
© Owned by the authors, published by EDP Sciences, 2014