Scalable and massively parallel Monte Carlo photon transport simulations for heterogeneous computing platforms

TL;DR

This paper introduces a scalable, vendor-independent Monte Carlo photon transport simulation platform optimized for heterogeneous systems, leveraging OpenCL for improved performance and portability across CPUs and GPUs.

Contribution

It develops a massively parallel, portable MC algorithm for heterogeneous platforms, extending GPU techniques with load-balancing strategies for diverse hardware.

Findings

Significantly improved simulation performance

Enhanced software portability across hardware platforms

Effective load-balancing strategies for CPUs and GPUs

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 (OpenCL) 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 strat- egies are developed to obtain efficient simulations using multiple central processing units (CPUs) and GPUs.