Abstract

Particle colliders are essential tools in the pursuit of understanding matter interactions in the universe. The tremendous cost of their operation and requirement for finetuning, make high-fidelity particle collider simulations essential in ensuring optimal operation. Simulations of the beam-beam effects of colliding particle bunches are extremely time-consuming since they include hundreds of billions of particles that collide millions of times per second. A high degree of parallelization is required to decrease the execution time of such simulations. GPUs present an opportunity towards making such simulations viable, though several challenges must be overcome in order to achieve efficient parallelization. One major challenge addressed in this paper is an efficient simulation of multiple bunch collision on a cluster of GPUs. The numerous colliding bunches are subject to scheduling constraints, which requires the utilization of an efficient collision schedule algorithm, all the while ensuring that the processors are not underutilized and communication overheads are low. We implemented two schemes on a 8-node cluster with four K40 GPUs on each node for a total of 32 GPUs. We demonstrated an almost linear speedup for large bunches with the number of GPUs.

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