Accelerating Dust Temperature Calculations with Graphics Processing Units

TL;DR

This paper demonstrates how using GPUs with CUDA significantly accelerates the calculation of dust grain temperatures in galaxy spectral energy distribution models, reducing computation time substantially.

Contribution

It introduces a GPU-based implementation of dust temperature calculations in the Sunrise code, achieving a 69-fold speedup over CPU-only methods.

Findings

GPU implementation is 69 times faster than CPU

Significant acceleration in galaxy SED calculations

Potential for more efficient radiation transfer modeling

Abstract

When calculating the infrared spectral energy distributions (SEDs) of galaxies in radiation-transfer models, the calculation of dust grain temperatures is generally the most time-consuming part of the calculation. Because of its highly parallel nature, this calculation is perfectly suited for massively parallel general-purpose Graphics Processing Units (GPUs). This paper presents an implementation of the calculation of dust grain equilibrium temperatures on GPUs in the Monte-Carlo radiation transfer code Sunrise, using the CUDA API. The GPU can perform this calculation 69 times faster than the 8 CPU cores, showing great potential for accelerating calculations of galaxy SEDs.