Videos & Podcasts

AI compiler support is one of the crucial enablers for any hardware system. It allows efficient mapping and execution of models on the device. The UXL interfaces enable unified access to different devices, a key...

The growing popularity of AI and analytics in virtually all domains has increased the amount of data gathered. Workflows have become increasingly heterogeneous. While CPUs are only sometimes efficient enough for the demands of modern...

The UXL Foundation projects have made lots of progress in the past year, with new features and releases. Maintainers from the projects will provide an update on what’s been happening in 2024 and what to...

The demand for heterogeneous architectures continues to rise, driven by the exponential growth in generative AI and accelerated computing. Workloads are being spread across new and diverse hardware, such as GPUs, NPUs, and AI accelerators,...

The demand for heterogeneous architectures continues to rise, driven by the exponential growth in generative AI and accelerated computing. Workloads are being spread across new and diverse hardware, such as GPUs, NPUs, and AI accelerators,...

The rise of edge computing has increased the need for portable hardware acceleration for AI and image processing, especially where power consumption matters or cloud connectivity is unreliable. Automotive drives software innovation in vehicles, particularly...