Heterogeneous concurrent execution of Monte Carlo photon transport on CPU, GPU and MIC

Abstract

In this paper, a new level of heterogeneous concurrent execution of Monte Carlo photon transport is presented. ARCHER, an application for computing radiation dosimetry for CT imaging involving whole-body patient phantoms has been extended to execute on any combination of CPUs, GPUs and MICs concurrently. The goal is for ARCHER to detect and simultaneously utilize all CPU, GPU and MIC processing devices available. Due to the irregular nature of the Monte Carlo photon transport algorithm, a new "self service" approach to organizing the heterogeneous device computing has been implemented. This approach efficiently and effectively allows each device to repeatedly grab portions of the domain and compute concurrently until the entire domain has been simulated. New timing benchmarks using various combinations of various Intel and NVIDIA devices are made and presented. A speedup of 13x has been observed when utilizing Intel's Xeon X5650 CPU, Intel's Xeon Phi 5110P MIC and NVIDIA's K40 GPU concurrently versus just the Intel Xeon X5650.