Heterogeneous particle-based simulation

Abstract

Particle-based simulations have been used to simulate granular materials, fluids, and rigid bodies. To achieve realistic behavior, a large number of particles have to be simulated. Particle-based simulations are suited for GPUs because the computation of each particle is almost the same, (i.e., the granularity of the computation is uniform over the particles). This is preferable for GPUs with a wide SIMD architecture. However, particle-based simulation on the GPU has been mostly restricted to simulating particles of identical size [Harada et al. 2007]. This is because the work granularity is non-uniform if there are particles with different radii, which leads to inefficient use of the GPU. Heterogeneous CPU/GPU architectures, such as AMD Fusion® APUs, can solve this simulation efficiently by using the CPU and the GPU at the same time. On a PC with a CPU and a discrete GPU, whenever a computation is dispatched to the GPU, the data has to be sent via PCI Express®bus, which introduces a latency. However, heterogeneous architectures have a CPU and a GPU on the same die with a tightly coupled shared memory, so the same memory space can be accessed from the GPU and the CPU without any copying, which can facilitate a tight collaboration between the two processors. In this paper, we describe a particle-based simulation with particles of various sizes running on a heterogeneous architecture by dispatching and simultaneously processing work on the GPU and CPU depending on the granularity.