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"The OpenVX Computer Vision and Neural Network Inference Library Standard for Portable, Efficient Code," a Presentation from AMD

Radhakrishna Giduthuri, Software Architect at Advanced Micro Devices (AMD), presents the "OpenVX Computer Vision and Neural Network Inference Library Standard for Portable, Efficient Code" tutorial at the May 2018 Embedded Vision Summit.

OpenVX is an industry-standard computer vision and neural network inference API designed for efficient implementation on a variety of embedded platforms. The API incorporates the concept of a dataflow graph, which enables implementers to apply a range of optimizations appropriate to their architectures, such as image tiling and kernel fusion. Application developers can use this API to create high-performance computer vision and AI applications quickly, without having to perform complex device-specific optimizations for data management and kernel execution, since these optimizations are handled by the OpenVX implementation provided by the processor vendor.

This talk describes the current status of OpenVX, with particular focus on neural network inference capabilities and the most recent enhancements. The talk concludes with summary of the currently available implementations and an overview of the roadmap for the OpenVX API and its implementations.