PSAL-POSTECH/PyTorchSim
PyTorchSim is a Comprehensive, Fast, and Accurate NPU Simulation Framework
This project helps evaluate the performance and efficiency of custom AI accelerator hardware designs, specifically Neural Processing Units (NPUs). It takes your existing PyTorch deep learning models (like ResNet, BERT, GPT-2) and produces detailed reports on how they would perform on a simulated NPU architecture. This is designed for hardware architects and system engineers developing new NPU designs.
Use this if you are designing or optimizing custom NPU hardware and need to accurately predict the performance and resource utilization of deep learning workloads before physical fabrication.
Not ideal if you are solely a deep learning practitioner focused on model development and training, or if you need to simulate general-purpose CPUs or GPUs.
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97
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17
Language
Python
License
MIT
Category
Last pushed
Mar 13, 2026
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