Scripts from Neural network inference on Pytorch with tools like ONNX, TensorRT, nvFuser, TorchDynamo, Triton
-
Updated
Nov 15, 2022 - Jupyter Notebook
#
torchdynamo
Here are 2 public repositories matching this topic...
The goal of the project is to benchmark and optimize BERT inference using different backends—PyTorch eager mode, TorchDynamo (Inductor backend), and NVIDIA Triton Inference Server. We use GLUE SST-2 samples for evaluation and compare performance through profiling, kernel timing, and latency analysis.
machine-learning machine-learning-algorithms pytorch high-performance-computing profiling bert nvidia-gpu hpml torchdynamo llm-inference nvidia-dynamo
-
Updated
May 10, 2025 - Jupyter Notebook
Improve this page
Add a description, image, and links to the torchdynamo topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the torchdynamo topic, visit your repo's landing page and select "manage topics."