标题： COSMICA：一种用于太阳系中宇宙射线传播的新型并行GPU代码 显示英文标题

标题： COSMICA: a novel parallel GPU code for Cosmic Rays propagation in heliosphere

摘要： 星际磁场的复杂结构及其由于太阳活动而产生的变化，使得必须通过数值模拟来计算宇宙射线（CR）的调制。用于快速蒙特卡罗（MC）模拟的代码，涉及CUDA架构（COSMICA）是一个MC代码，用于向后求解等效于帕克输运方程（PTE）的随机微分方程（SDE）系统。COSMICA代码的图形处理单元（GPU）并行化是该领域的一个突破，因为它将标准模拟的计算时间从数百分钟减少到几分钟。此外，该代码能够在具有多个GPU的机器集群上分布计算，为扩展打开了道路。在COSMICA中，我们实现了同步广播内存访问以演化变量样本，对虚拟粒子集数量进行四舍五入以满足GPU块，并利用共享内存来释放寄存器。此外，我们简化了数学计算，并转为更轻量级的动量公式。该代码首次移植到GPU架构上带来了40倍的速度提升。成功的优化带来了1.5倍的速度提升。 显示英文摘要

摘要： The complex structure of interplanetary magnetic fields and their variability, due to solar activity, make it necessary to compute the Cosmic Ray (CR) modulation with numerical simulations. COde for a Speedy Monte Carlo (MC) Involving Cuda Architecture (COSMICA) is a MC code, solving backward-in-time the system of Stochastic Differential Equations (SDE) equivalent to the Parker Transport Equation (PTE). The Graphics Processing Unit (GPU) parallelization of COSMICA code is a game changer in this field because it reduces the computational time of a standard simulation from the order of hundred of minutes to few of them. Furthermore, the code is capable of distributing the computations on clusters of machines with multiple GPUs, opening the way for scaling. In COSMICA we implemented the synchronous broadcasting of memory access for evolving variable samples, the rounding of virtual particle set numbers, to fulfil the GPU blocks, and the exploitation of shared memory to free registers. Furthermore, we compactify the mathematical computations and pass to the lighter momentum formulation of SDE. The first porting of the code on GPU architecture brings it to a speed-up of 40X. The successful optimizations bring 1.5X speed-up.