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This content will become publicly available on May 27, 2025

Title: Automating GPU Scalability for Complex Scientific Models: Phonon Boltzmann Transport Equation
Heterogeneous computing environments combining CPU and GPU resources provide a great boost to large-scale scientific computing applications. Code generation utilities that partition the work into CPU and GPU tasks while considering data movement costs allow researchers to develop high-performance solutions more quickly and easily, and make these resources accessible to a larger user base.We present developments for a domain-specific language (DSL) and code generation framework for solving partial differential equations (PDEs). These enhancements facilitate GPU-accelerated solution of the Boltzmann transport equation (BTE) for phonons, which is the governing equation for simulating thermal transport in semiconductor materials at sub-micron scales. The solution of the BTE involves thousands of coupled PDEs as well as complicated boundary conditions and solving a nonlinear equation that couples all of the degrees of freedom at each time step. These developments enable the DSL to generate configurable hybrid GPU/CPU code that couples accelerated kernels with user-defined code. We observed performance improvements of around 18X compared to a CPU-only version produced by this same DSL with minimal additional programming effort.  more » « less
Award ID(s):
2004236
PAR ID:
10556067
Author(s) / Creator(s):
; ; ; ;
Publisher / Repository:
IEEE
Date Published:
ISBN:
979-8-3503-8711-7
Page Range / eLocation ID:
430 to 439
Format(s):
Medium: X
Location:
San Francisco, CA, USA
Sponsoring Org:
National Science Foundation
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