Calculation of Stochastic Heating and Emissivity of Cosmic Dust Grains with Optimization for the Intel Many Integrated Core Architecture
Troy A. Porter, Andrey E. Vladimirov

TL;DR
This paper introduces HEATCODE, a highly optimized computational library for modeling stochastic heating and emissivity of cosmic dust grains, significantly improving performance on Intel MIC architecture and general-purpose processors.
Contribution
The paper presents HEATCODE, a new library optimized for Intel MIC architecture and multi-core processors, enabling efficient dust emission calculations in radiation transport models.
Findings
HEATCODE achieves approximately twice the performance of standard multicore systems.
The library efficiently runs on co-processor cards and supports heterogeneous calculations.
Optimization steps significantly improved code performance on Intel MIC architecture.
Abstract
Cosmic dust particles effectively attenuate starlight. Their absorption of starlight produces emission spectra from the near- to far-infrared, which depends on the sizes and properties of the dust grains, and spectrum of the heating radiation field. The near- to mid-infrared is dominated by the emissions by very small grains. Modeling the absorption of starlight by these particles is, however, computationally expensive and a significant bottleneck for self-consistent radiation transport codes treating the heating of dust by stars. In this paper, we summarize the formalism for computing the stochastic emissivity of cosmic dust, which was developed in earlier works, and present a new library HEATCODE implementing this formalism for the calculation for arbitrary grain properties and heating radiation fields. Our library is highly optimized for general-purpose processors with multiple cores…
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Taxonomy
TopicsRadiation Effects in Electronics · Spacecraft Design and Technology · Radiative Heat Transfer Studies
