Advancing Embedded Vision Systems: Harnessing Hardware Acceleration and Open Standards

Offloading processing to accelerators enables embedded vision systems to process workloads that exceed the capabilities of CPUs. However, parallel processors adds complexity as workloads must be distributed and synchronized across processing resources. Proven open standard APIs and languages can significantly streamline the design and programming of parallel processing systems, avoiding the need for companies to independently create and support an entire ecosystem of processors, tooling, developer education and supporting third-party libraries and machine learning stacks. In addition, effective open standards separate hardware and software development, enabling systems to integrate new components with ease, for cross-generation reusability and field upgradability. In this session, we will give an update on Khronos Group open standards for programming and deploying accelerated inferencing, embedded vision and safety-critical systems, including the in-development Kamaros open standard API for embedded camera systems.