Graphic processors to speed-up simulations for the design of high performance solar receptors

TL;DR

This paper demonstrates how GPUs can significantly accelerate simulations for designing high-performance solar receptors, focusing on radiative heat transfer calculations using Monte Carlo ray-tracing.

Contribution

It introduces a GPU-accelerated prototype for simulating radiative heat transfer in solar receptor design, achieving over 400x speed-up compared to CPU implementations.

Findings

GPU-based computations are over 400 times faster than CPU counterparts.

GPU floating point accuracy was evaluated through tests and surveys.

The prototype effectively integrates into simulation codes for solar receptor design.

Abstract

Graphics Processing Units (GPUs) are now powerful and flexible systems adapted and used for other purposes than graphics calculations (General Purpose computation on GPU -- GPGPU). We present here a prototype to be integrated into simulation codes that estimate temperature, velocity and pressure to design next generations of solar receptors. Such codes will delegate to our contribution on GPUs the computation of heat transfers due to radiations. We use Monte-Carlo line-by-line ray-tracing through finite volumes. This means data-parallel arithmetic transformations on large data structures. Our prototype is inspired on the source code of GPUBench. Our performances on two recent graphics cards (Nvidia 7800GTX and ATI RX1800XL) show some speed-up higher than 400 compared to CPU implementations leaving most of CPU computing resources available. As there were some questions pending about the accuracy of the operators implemented in GPUs, we start this report with a survey and some contributed tests on the various floating point units available on GPUs.