Arhat is a cross-platform deep learning framework that converts neural network descriptions into lean standalone executable code. This approach provides significant benefits because of a simple and straightforward deployment process.
Arhat is integrated with Intel oneAPI deep learning libraries. Arhat backend for Intel generates C++ code that directly calls oneDNN API. Furthermore, Arhat provides a module that consumes models produced by the OpenVINO Model Optimizer.
I will present recent case studies dedicated to using Arhat for building object detection applications on Intel CPU and GPU hardware. These studies cover models from OpenVINO Model Zoo as well as models from Detectron2 library.

 

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