Accelerating Monte Carlo Transport in the Trade-off of Performance and Power

Abstract

Random simulation for particle transport theory is the main method for solving particle transport questions, which is widely used in medicine and computational physics. In this work, we present a multi-core reconfigurable architecture that aims to meet the performance per watt requirements of future Domain Specific Architectures (DSAs). The architecture proposed in this paper consists of heterogeneous lightweight cores, a reconfigurable cache structure, and High Bandwidth Memory. By targeting the different feature requirements of the Monte Carlo transport code at different stages, we design more necessary and efficient features for the lightweight calculating core, and continue to provide a trade-off of performance and energy consumption through reconfiguration. We designed and validated the accelerator architecture using gem5. Experiments show that compared with the traditional architecture composed of multiple out-of-order core, this architecture can obtain more than 3x in performance per watt. Some conclusions explored are not limited to the architecture proposed in this paper, but lay the foundation for further studies of large-scale transport accelerators.