This paper describes the main features of a pioneering unsteady solver for simulating ideal two-fluid plasmas on unstructured grids, taking profit of GPGPU (General-purpose computing on graphics processing units). The code, which has been implemented within the open source COOLFluiD platform, is implicit, second-order in time and space, relying upon a Finite Volume method for the spatial discretization and a three-point backward Euler for the time integration. In particular, the convective fluxes are computed by a multi-fluid version of the AUSM+up scheme for the plasma equations, in combination with a modified Rusanov scheme with tunable dissipation for the Maxwell equations. Source terms are integrated with a one-point rule, using the cell-centered value. Some critical aspects of the porting to GPU's are discussed, as well as the performance of two open source linear system solvers (i.e. PETSc, PARALUTION). The code design allows for computing both flux and source terms on the GPU along with their Jacobian, giving a noticeable decrease in the computational time in comparison with the original CPU-based solver. The code has been tested in a wide range of mesh sizes and in three different systems, each one with a different GPU. The increased performance (up to 14x) is demonstrated in two representative 2D benchmarks: propagation of circularly polarized waves and the more challenging Geospace Environmental Modeling (GEM) magnetic reconnection challenge.
Heterogeneous Computing on Mixed Unstructured Grids with PyFR
PyFR是一个开源的高阶精确计算流体动力学求解器，用于混合非结构化网格，可以从单个代码库针对一系列硬件平台。在本文中，我们证明了PyFR的能力，使用异构多节点硬件的混合非结构化网格上进行高阶精确的非定常模拟流。具体而言，在对各种平台的单节点性能进行基准测试后，PyFR v0.2.2用于在雷诺数为3900的圆柱体上进行非定常流的模拟，该模拟使用了包含Intel Xeon E5-2697 v2 CPU、NVIDIA Tesla K40 c GPU和AMD FirePro W 9100 GPU的台式工作站上的棱柱体和四面体元素的混合非结构化网格。PyFR的性能和准确性进行了评估。PyFR v0.2.2可以在3-Clause New Style BSD许可证下免费获得（参见www.pyfr.org）。
