Scalable and massively parallel Monte Carlo photon transport simulations for heterogeneous computing platforms
arXiv:1711.03244 · doi: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 (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.
Accepted for Publication in Journal of Biomedical Optics Letters on Jan 4, 2018, to appear in Volume 23, Issue 2
Cited by in corpus (4)
- Estimation of blood oxygenation with learned spectral decoloring for quantitative photoacoustic imaging (LSD-qPAI)
- A transportable hyperspectral imaging setup based on fast, high-density spectral scanning for in situ quantitative biochemical mapping of fresh tissue biopsies
- 3D Monte Carlo Simulation of Light Distribution in Mouse Brain in Quantitative Photoacoustic Computed Tomography
- Monte Carlo modeling photon-tissue interaction using on-demand cloud infrastructure