OpenTM: An Open-source, Single-GPU, Large-scale Thermal Microstructure Design Framework

TL;DR

OpenTM is an open-source framework enabling efficient design of high-resolution thermal microstructures on a single GPU, making advanced thermal material design accessible and practical for educational and research purposes.

Contribution

It introduces a GPU-based, open-source framework with adaptive volume fraction and stable OC method for designing thermal microstructures efficiently.

Findings

High-resolution structures generated in under 90 seconds

Low GPU memory usage of 355 MB

Accessible Python interface for ease of use

Abstract

Thermal microstructures are artificially engineered materials designed to manipulate and control heat flow in unconventional ways. This paper presents an educational framework, called \emph{OpenTM}, to use a single GPU for designing periodic 3D high-resolution thermal microstructures to match the predefined thermal conductivity matrices with volume fraction constraints. Specifically, we use adaptive volume fraction to make the Optimality Criteria (OC) method run stably to obtain the thermal microstructures without a large memory overhead.Practical examples with a high resolution $128 \times 128 \times 128$ run under 90 seconds per structure on an NVIDIA GeForce GTX 4070Ti GPU with a peak GPU memory of 355 MB. Our open-source, high-performance implementation is publicly accessible at \url{https://github.com/quanyuchen2000/OPENTM}, and it is easy to install using Anaconda. Moreover, we provide a Python interface to make OpenTM well-suited for novices in C/C++.