PyPOD-GP: Using PyTorch for accelerated chip-level thermal simulation of the GPU
The rising demand for high-performance computing (HPC) has made full-chip dynamic thermal simulation in many-core GPUs critical for optimizing performance and extending device lifespans. Proper orthogonal decomposition (POD) with Galerkin projection (GP) has shown to offer high accuracy and massive...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-05-01
|
| Series: | SoftwareX |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352711025001141 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849761935530131456 |
|---|---|
| author | Neil He Ming-Cheng Cheng Yu Liu |
| author_facet | Neil He Ming-Cheng Cheng Yu Liu |
| author_sort | Neil He |
| collection | DOAJ |
| description | The rising demand for high-performance computing (HPC) has made full-chip dynamic thermal simulation in many-core GPUs critical for optimizing performance and extending device lifespans. Proper orthogonal decomposition (POD) with Galerkin projection (GP) has shown to offer high accuracy and massive runtime improvements over direct numerical simulation (DNS). However, previous implementations of POD-GP use MPI-based libraries like PETSc and FEniCS and face significant runtime bottlenecks. We propose a PyTorch-based POD-GP library (PyPOD-GP), a GPU-optimized library for chip-level thermal simulation. PyPOD-GP achieves over 23.4× speedup in training and over 10× speedup in inference on a GPU with over 13,000 cores, with just 1.2% error over the device layer. |
| format | Article |
| id | doaj-art-01016b463d3d4b8bb3bce12e35284a73 |
| institution | DOAJ |
| issn | 2352-7110 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | SoftwareX |
| spelling | doaj-art-01016b463d3d4b8bb3bce12e35284a732025-08-20T03:05:52ZengElsevierSoftwareX2352-71102025-05-013010214710.1016/j.softx.2025.102147PyPOD-GP: Using PyTorch for accelerated chip-level thermal simulation of the GPUNeil He0Ming-Cheng Cheng1Yu Liu2Department of Mathematics, Yale University, United States of AmericaDepartment of Electrical and Computer Engineering, Clarkson University, United States of AmericaDepartment of Electrical and Computer Engineering, Clarkson University, United States of America; Corresponding author.The rising demand for high-performance computing (HPC) has made full-chip dynamic thermal simulation in many-core GPUs critical for optimizing performance and extending device lifespans. Proper orthogonal decomposition (POD) with Galerkin projection (GP) has shown to offer high accuracy and massive runtime improvements over direct numerical simulation (DNS). However, previous implementations of POD-GP use MPI-based libraries like PETSc and FEniCS and face significant runtime bottlenecks. We propose a PyTorch-based POD-GP library (PyPOD-GP), a GPU-optimized library for chip-level thermal simulation. PyPOD-GP achieves over 23.4× speedup in training and over 10× speedup in inference on a GPU with over 13,000 cores, with just 1.2% error over the device layer.http://www.sciencedirect.com/science/article/pii/S2352711025001141GPU thermal simulationProper Orthogonal Decomposition (POD)Finite element methodPyTorchGalerkin projection |
| spellingShingle | Neil He Ming-Cheng Cheng Yu Liu PyPOD-GP: Using PyTorch for accelerated chip-level thermal simulation of the GPU SoftwareX GPU thermal simulation Proper Orthogonal Decomposition (POD) Finite element method PyTorch Galerkin projection |
| title | PyPOD-GP: Using PyTorch for accelerated chip-level thermal simulation of the GPU |
| title_full | PyPOD-GP: Using PyTorch for accelerated chip-level thermal simulation of the GPU |
| title_fullStr | PyPOD-GP: Using PyTorch for accelerated chip-level thermal simulation of the GPU |
| title_full_unstemmed | PyPOD-GP: Using PyTorch for accelerated chip-level thermal simulation of the GPU |
| title_short | PyPOD-GP: Using PyTorch for accelerated chip-level thermal simulation of the GPU |
| title_sort | pypod gp using pytorch for accelerated chip level thermal simulation of the gpu |
| topic | GPU thermal simulation Proper Orthogonal Decomposition (POD) Finite element method PyTorch Galerkin projection |
| url | http://www.sciencedirect.com/science/article/pii/S2352711025001141 |
| work_keys_str_mv | AT neilhe pypodgpusingpytorchforacceleratedchiplevelthermalsimulationofthegpu AT mingchengcheng pypodgpusingpytorchforacceleratedchiplevelthermalsimulationofthegpu AT yuliu pypodgpusingpytorchforacceleratedchiplevelthermalsimulationofthegpu |