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

Leiming Yu; Fanny Nina-Paravecino; David R. Kaeli; Qianqian Fang

doi:10.1117/1.JBO.23.1.010504

26 January 2018 Scalable and massively parallel Monte Carlo photon transport simulations for heterogeneous computing platforms

Leiming Yu, Fanny Nina-Paravecino, David R. Kaeli, Qianqian Fang

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Journal of Biomedical Optics, Vol. 23, Issue 1, 010504 (January 2018). https://doi.org/10.1117/1.JBO.23.1.010504

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.

CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Leiming Yu, Fanny Nina-Paravecino, David R. Kaeli, and Qianqian Fang "Scalable and massively parallel Monte Carlo photon transport simulations for heterogeneous computing platforms," Journal of Biomedical Optics 23(1), 010504 (26 January 2018). https://doi.org/10.1117/1.JBO.23.1.010504

Received: 4 November 2017; Accepted: 4 January 2018; Published: 26 January 2018

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