oneAPI is a unified application programming interface intended to be used across different compute accelerator architectures, including CPUs, GPUs and AI accelerators. It's aim is to unify the programming model as well as simplifying cross-architecture development. It also provides libraries for:
- deep neural network (DNN) learning applications,
- collective communications for machine learning and deep learning projects, and,
- data analytics making big data analysis faster using optimized algorithms.
By the end of this workshop one will have:
- learned about oneAPI libraries and the inference toolkit, components, and capabilities for developing and deploying computer vision and deep learning solutions,
- explored techniques for optimizing pre-trained deep learning models and learn how to work with models from different frameworks like Tensorflow, PyTorch and Caffe,
- understood how to perform inference on different hardware such as CPU and GPU, and,
- considered practical computer vision applications and use cases.
Level: Intermediate
Length: 3 Hours
Format: Lecture + Hands-on
Prerequisites:
- Attendees having hands-on experience with Python and some experience with Tensorflow or PyTorch will get the most out of this workshop.
- Teacher: Peter Darveau