一种高效的混合精度混合CPU-GPU全隐式粒子网格算法实现
An efficient mixed-precision, hybrid CPU-GPU implementation of a fully implicit particle-in-cell algorithm
摘要：
最近，一种全隐式的、能量和电荷守恒的粒子网格法被提出用于多尺度、全f动力学模拟[G. Chen等人，J. Comput. 230，18（2011）]。该方法采用无雅可比牛顿-克雷洛夫（JFNK）求解器，能够使用非常大的时间步长，而不会损失数值稳定性或精度。该方法的一个基本特征是粒子轨道计算与场求解器分离，同时保持完全自洽。本文描述了一个非常有效的，混合精度的混合CPU-GPU实现的隐式PIC算法利用这一功能。JFNK求解器以双精度（DP）保存在CPU上，而隐式、电荷保存和自适应粒子移动器则使用CUDA以单精度（SP）在GPU（图形处理单元）上实现。性能为导向的优化介绍了与援助的屋顶模型。隐式粒子移动器算法在Nvidia GeForce GTX 580上实现高达400 GOp/s。这相当于25%的绝对GPU效率与峰值理论性能相比，并且比等效的串行CPU（Intel Xeon X5460）执行速度快约300倍。对于所选的测试用例，混合精度的混合CPU-GPU求解器表现出超过DP CPU仅串行版本的\sim 100倍，在具有挑战性的长时间尺度离子声波模拟中没有明显的鲁棒性或准确性损失。
英文摘要：
Recently, a fully implicit, energy- and charge-conserving particle-in-cell method has been proposed for multi-scale, full-f kinetic simulations [G. Chen, et al., J. Comput. Phys. 230,18 (2011)]. The method employs a Jacobian-free Newton-Krylov (JFNK) solver, capable of using very large timesteps without loss of numerical stability or accuracy. A fundamental feature of the method is the segregation of particle-orbit computations from the field solver, while remaining fully self-consistent. This paper describes a very efficient, mixed-precision hybrid CPU-GPU implementation of the implicit PIC algorithm exploiting this feature. The JFNK solver is kept on the CPU in double precision (DP), while the implicit, charge-conserving, and adaptive particle mover is implemented on a GPU (graphics processing unit) using CUDA in single-precision (SP). Performance-oriented optimizations are introduced with the aid of the roofline model. The implicit particle mover algorithm is shown to achieve up to 400 GOp/s on a Nvidia GeForce GTX580. This corresponds to 25% absolute GPU efficiency against the peak theoretical performance, and is about 300 times faster than an equivalent serial CPU (Intel Xeon X5460) execution. For the test case chosen, the mixed-precision hybrid CPU-GPU solver is shown to over-perform the DP CPU-only serial version by a factor of \sim 100, without apparent loss of robustness or accuracy in a challenging long-timescale ion acoustic wave simulation.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
