Have you checked out awesome-oneapi?

Are you looking for inspiration and examples of how to accelerate AI, graphics, and scientific computing applications across CPUs and GPUs with a seamless developer experience? Check out awesome-oneapi - a GitHub community featuring a curated list of projects using the oneAPI programming model!

oneAPI is an open, cross-industry, standards-based, unified, multiarchitecture, and multivendor programming model that delivers a common developer experience across accelerator architectures – CPUs, GPUs, FPGAs – for faster application performance, more productivity, and greater innovation.

The awesome-oneapi community showcases over 189 high-quality projects plus instructive tutorials to help developers get started with their own projects.

There are over 84 AI related projects in categories covering computer vision, data science, machine learning, natural language processing, and frameworks and toolkits. Some examples:

• In the Computer Vision category, get access to a Stable Diffusion repository containing models trained from scratch and continuously updated.
• The Natural Language Processing category contains a cool Python-based Language Identification  sample that shows how to train a model to perform language identification using the Hugging Face Speechbrain library and CommonVoice dataset, and optimized with Intel® Extension for PyTorch and Intel® Neural Compressor.
• Frameworks and Toolkits include a Product Recommendation reference kit that demonstrates one way where AI can be used to build a recommendation system for an e-commerce business using scikit-learn and oneAPI.

In the realm of data visualization and rendering, 22 projects include open source libraries developed by Intel including:

• Embree – a high-performance ray tracing library developed by Intel that targets graphics application developers to improve the performance of photo-realistic rendering applications and offers support for both CPUs and GPUs, while maintaining one code base to improve productivity and eliminate inconsistencies between the two versions of the renderer.
• Intel® Open Image Denoise – an open-source library for image denoising in ray tracing rendering applications with high quality and performance, thanks to efficient deep learning-based filters that can be trained using the included toolkit and user-provided image datasets.
• The Intel® Open Path Guiding Library (Open PGL) implements path guiding into a renderer, offering implementations of current state-of-the-art path guiding methods which increase the sampling quality and renderer efficiency.
• OSPRay – an open source, scalable and portable ray tracing engine designed for high fidelity visualization on Intel architecture CPUs. It allows users to easily build interactive applications using ray-tracing based rendering for both surface and volume-based visualizations.
• LightWave Explorer – an open source nonlinear optics simulator, intended to be fast, visual, and flexible for students and researchers to play with ultrashort laser pulses and nonlinear optics without having to buy a laser first. It’s the first distributable app that is available on the Linux app store that anybody can download.

In the Mathematics and Science category, users can access 31 projects including some of the most consequential initiatives in biosciences such as Amber, GROMACS, LAMMPS, and NAMD – as well as physics applications such as 1D Heat Transfer Simulation , 3D Wave Simulation , and ATLAS Charged Particle Seed Finding with DPC++. 

Whatever your project, check out awesome-oneapi for code samples to jump-start your solution!

Get a quick intro to oneAPI in this video and explore the latest Intel® Software Development Tools