Microsoft ONNX Runtime is an open source inference accelerator focused on ONNX models. It is the platform Vitis AI has integrated with to provide first-class ONNX model support, which can be exported from a wide variety of training frameworks. It incorporates very easy to use runtime APIs in Python and C++ and can support models without requiring the separate compilation phase that TVM requires. Included in ONNXRuntime is a partitioner that can automatically partition between the CPU and FPGA further enhancing the ease of model deployment. Finally, it also incorporates the Vitis AI quantizer in a way that does not require separate quantization setup.
To read more about Microsoft ONNX Runtime, see https://microsoft.github.io/onnxruntime/.
Vitis AI provides tutorials and installation guides on Vitis AI and ONNX Runtime integration on the Vitis AI GitHub repository: https://github.com/Xilinx/Vitis-AI/tree/v3.0/third_party/onnxruntime.