Abstract
.We present a highly scalable Monte Carlo (MC) three-dimensional photon transport simulation platform designed for heterogeneous computing systems. Through the development of a massively parallel MC algorithm using the Open Computing Language framework, this research extends our existing graphics processing unit (GPU)-accelerated MC technique to a highly scalable vendor-independent heterogeneous computing environment, achieving significantly improved performance and software portability. A number of parallel computing techniques are investigated to achieve portable performance over a wide range of computing hardware. Furthermore, multiple thread-level and device-level load-balancing strategies are developed to obtain efficient simulations using multiple central processing units and GPUs.
Highlights
We present a highly scalable Monte Carlo (MC) three-dimensional photon transport simulation platform designed for heterogeneous computing systems
Most graphics processing unit (GPU)-based MC photon transport frameworks reported in the literature,[3,4,5,6,7] including Monte Carlo eXtreme (MCX), have been written exclusively using the CUDA programming model developed by NVIDIA.[8]
Because CUDA is targeted for NVIDIA GPUs, most existing GPU MC codes cannot be executed on a central processing unit (CPU) or a high-performance GPU made by other manufacturers
Summary
We present a highly scalable Monte Carlo (MC) three-dimensional photon transport simulation platform designed for heterogeneous computing systems. Most GPU-based MC photon transport frameworks reported in the literature,[3,4,5,6,7] including MCX, have been written exclusively using the CUDA programming model developed by NVIDIA.[8] Because CUDA is targeted for NVIDIA GPUs, most existing GPU MC codes cannot be executed on a central processing unit (CPU) or a high-performance GPU made by other manufacturers. This work aims to improve and generalize our previously developed massively parallel photon transport simulation platform through the adoption of a heterogeneous computing framework using the OpenCL programming model.
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