A platform-oblivious approach for heterogeneous computing: A case study with Monte Carlo-based simulation for medical applications

Light is important and helpful in many medical applica- tions, 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 meth- ods 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 lim- ited portability and prolongs software updates. In this pa- per, we parallelize the Monte Carlo modeling of light trans- port 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.