A Platform-Oblivious Approach for Heterogeneous Computing: A Case Study with Monte Carlo-based Simulation for Medical Applications

Abstract

Light is important and helpful in many medical applications, such as cancer treatment. Computer modeling and simulation of light transport are often adopted to improve the quality of medical treatments. In particular, Monte Carlo-based simulations are considered to deliver accurate results, but require intensive computational resources. While several attempts to accelerate the Monte Carlo-based methods for the simulation of photon transport with platform-specific programming schemes, such as CUDA on GPU and HDL on FPGA, have been proposed, the approach has limited portability and prolongs software updates. In this paper, we parallelize the Monte Carlo modeling of light transport in multi-layered tissues (MCML) program with OpenCL, an open standard supported by a wide range of platforms. We characterize the performance of the parallelized MCML kernel program runs on CPU, GPU and FPGA. Compared to platform-specific programming schemes, our platform-oblivious approach provides a unified, highly portable code and delivers competitive performance and power efficiency.