APIs for Accelerating Vision and Inferencing: an Industry Overview of Options and Trade-offs

Summit Track: 
Technical Insights I

The landscape of SDKs, APIs and file formats for accelerating inferencing and vision applications continues to evolve rapidly. Low-level compute APIs, such as OpenCL, Vulkan and CUDA are being used to accelerate inferencing engines such as OpenVX, CoreML, NNAPI and TensorRT, being fed by neural network file formats such as NNEF and ONNX. Some of these APIs, like OpenCV, are vision-specific, while others, like OpenCL, are general-purpose. Some engines, like CoreML and TensorRT, are supplier-specific, while others such as OpenVX, are open standards that any supplier can adopt. Which ones should you use for your project?


Neil Trevett

President, Khronos Group

At NVIDIA Neil works to enable applications leverage advanced silicon acceleration. Neil is also the elected President of the Khronos Group where he has helped initiate and evolve APIs and formats such as Vulkan, OpenXR, OpenGL ES, WebGL, glTF, OpenCL, OpenVX and NNEF

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