标题： 在图形处理单元上具有复杂动力学的流动求解器的开发 显示英文标题

标题： Development of a Flow Solver with Complex Kinetics on the Graphic Processing Units

摘要： 本文报告了在图形处理单元（GPU）上实现数值求解器，以模拟具有详细化学动力学的反应气体混合物。该求解器结合了高阶有限体积方法来求解与刚性源项耦合的流体动力学方程。化学动力学通过操作符分裂方法隐式求解。我们探索了在GPU上实现快速动力学求解器的不同方法。本文讨论了实现的细节。该求解器使用两种高阶激波捕捉方案进行测试：MP5（Suresh等，1997）和ADERWENO（Titarev等，2005）。仅考虑流体动力学计算，得到的速度提升因子分别为MP5方案的30倍和ADERWENO方案的55倍。对于完全耦合的求解器，性能提升取决于反应机制的大小。探讨了两种不同的化学机制。第一个机制包含9种物质和38个反应，速度提升因子最高可达35。第二个更大的机制包含36种物质和308个反应，速度提升因子最高可达40。 显示英文摘要

摘要： The current paper reports on the implementation of a numerical solver on the Graphic Processing Units (GPU) to model reactive gas mixture with detailed chemical kinetics. The solver incorporates high-order finite volume methods for solving the fluid dynamical equations coupled with stiff source terms. The chemical kinetics are solved implicitly via an operator-splitting method. We explored different approaches in implementing a fast kinetics solver on the GPU. The detail of the implementation is discussed in the paper. The solver is tested with two high-order shock capturing schemes: MP5 (Suresh, et al. (1997)) and ADERWENO (Titarev, et al. (2005)). Considering only the fluid dynamics calculation, the speed-up factors obtained are 30 for the MP5 scheme and 55 for ADERWENO scheme. For the fully-coupled solver, the performance gain depended on the size of the reaction mechanism. Two different examples of chemistry were explored. The first mechanism consisted of 9 species and 38 reactions, resulting in a speed-up factor up to 35. The second, larger mechanism consisted of 36 species and 308 reactions, resulting in a speed-up factor of up to 40.