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Area of Science:

  • Materials Science
  • Computational Physics
  • Solid-State Physics

Background:

  • Lattice thermal conductivity (LTC) is crucial for technological applications.
  • The Peierls-Boltzmann transport equation (PBTE) reveals phonon transport properties but is computationally intensive.
  • Accelerating PBTE calculations is essential for complex materials and high-order phonon scattering.

Purpose of the Study:

  • To develop a new, GPU-optimized algorithm for accurate and efficient LTC calculations.
  • To create an open-source code, GPU_PBTE, based on the proposed algorithm.
  • To demonstrate the performance and reliability of GPU_PBTE for materials like silicon and silicon carbide.

Main Methods:

  • Developed a novel algorithm specifically optimized for GPU architecture, employing a two-kernel method to prevent divergent branching.
  • Implemented the algorithm into an open-source software package named GPU_PBTE.
  • Validated the code by calculating the thermal transport properties of silicon and silicon carbide.

Main Results:

  • GPU_PBTE achieves accurate and reliable LTC calculations.
  • The software demonstrates a significant speedup, being two to three orders of magnitude faster than a CPU-based version on high-performance hardware (NVIDIA Tesla V100 vs. Intel Xeon CPU Gold 6248).
  • The study highlights the potential for accelerating scientific simulations on novel hardware platforms.

Conclusions:

  • The developed GPU_PBTE code offers a substantial acceleration for LTC computations.
  • This work enables more efficient investigation of phonon transport properties in complex materials.
  • The approach provides a framework for future hardware-accelerated scientific simulations.