Scalable Solution of Radiative Heat Transfer Problems by the Photon Monte Carlo Algorithm on Hybrid Computing Architectures

The simulation of Radiative Heat Transfer (RHT) effects by the Photon Monte Carlo (PMC) method is a computationally demanding problem. In this paper we present results and analysis of a new algorithm designed to solve this problem on a hybrid computing architecture. This architecture includes distributed memory, shared memory, and Graphics Processing Unit (GPU) accelerated components. In this paper we present an approach to obtain good parallel performance based on a partitioning of the application software into two parts. The first part is a multithreaded application code that manages the ray tracing aspects of the PMC. The second part is an asynchronous, GPU-accelerated pseudo-random number generation library. An advantage of this approach is that this software framework can be easily translated to other Monte Carlo applications. We present experimental results from a largescale hybrid computer for a standard RHT model problem and compare these results to our analytical model.