Introduction

The TT-Forge-ONNX is a graph compiler designed to optimize and transform computational graphs for deep learning models on single-chip systems, enhancing their performance and efficiency.

Built on top of the TT-MLIR backend, TT-Forge-ONNX is an integral component of the TT-Forge project, which provides a comprehensive suite of tools for optimizing and deploying deep learning models on Tenstorrent hardware.

The main project goals are:

• Provide abstraction of ONNX, TensorFlow, and PaddlePaddle frontend frameworks

• Compile many kinds of model architectures without custom modification and with great performance (for example, Transformers, CNNs, etc.)

• Abstract all Tenstorrent device architectures (for example, Wormhole, Blackhole, etc.)