Development of scalable GPU-based direct whole-core depletion calculation methods

Abstract

GPU (Graphical Processing Unit) acceleration methods are introduced to the depletion solver and the cross section (XS) calculation routines of the direct whole core calculation code, nTRACER, for scalable and superior computing performance. Extensive GPU acceleration besides transport solvers is necessary to resolve the performance degradation in depletion calculations caused by the newly generated nuclides in depleted fuel regions and the poor scalability. A matrix exponential solver employing the Gauss-Seidel-based Chebyshev rational approximate method is implemented to reduce branch divergence and load imbalance in GPU computing in the solution of the Bateman equation. A non-zero element major storage scheme is developed to optimize memory access efficiency on GPUs by exploiting the same sparsity pattern of the depletion matrix in all the depletion regions. XS data are serialized for effective massive parallelization of XS calculation on GPUs. A block decomposition scheme for XS calculation is implemented to reduce the global memory requirement due to the limited memory capacity of commercial GPUs. It is demonstrated that nTRACER can complete a direct whole core depletion calculation for a realistic core in a few hours on a moderate-sized GPU-based heterogeneous computing platform after extensive GPU porting to all the essential routines.