Accelerating machine learning and AI workloads often requires specialized hardware, but managing compatibility across diverse platforms can be challenging. The Khronos Group provides the industry’s only suite of nonproprietary API and language standards for ML and AI acceleration, enabling developers to build flexible, portable and scalable solutions. This session will explore how Khronos APIs such as Vulkan, OpenCL, SYCL and OpenVX empower developers to optimize AI workloads across GPUs, NPUs and FPGAs while ensuring portability across vendors. We will also highlight recent advancements like the open-source Slang shading language for neural computation and the evolving OpenVX framework for cross-vendor inferencing. Discover how Khronos is shaping the future of AI and ML acceleration by fostering open ecosystems that reduce deployment complexity, enhance hardware interoperability and lower development costs, including in embedded and safety-critical systems.
Deploying Accelerated ML and AI: The Role of Khronos Open Standards
Session Speakers
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Neil Trevett
President, Khronos Group
Neil Trevett has served as the elected president of the Khronos Group for more than 20 years and most recently founded and now serves as the President and Chairman of the Metaverse Standards Forum. The Khronos Group, a nonprofit standards development organization (SDO), has been working on “metaverse tech” for 20 years. Neil has been at the forefront of the 3D and metaverse revolution bringing interactive 3D to mobile and the PC. He is also Vice President of Developer Ecosystems at NVIDIA, where he helps enable applications to take advantage of advanced GPU and silicon acceleration. At Khronos, Neil initiated the OpenGL ES standard now used by billions worldwide every day, helped catalyze the WebGL project to bring interactive 3D graphics to the Web, fostered the creation of the glTF standard for 3D assets, helped establish and launch the new-generation Vulkan API and chairs the OpenCL working group defining the open standard for heterogeneous parallel computation.
