Training for oneAPI
Learn the way you want with learning paths, tools training, webinars, and more.
Learn the fundamentals of Data Parallel C++ (DPC++) programming in a heterogeneous environment where a CPU, GPU, FPGA, or accelerator can be programmed to work together or in isolation.
The language and API extensions in DPC++ enable different development use cases.
- Develop new offload acceleration or heterogeneous computer applications
- Convert existing C or C++ code to SYCL and DPC++
- Migrate your code from other accelerator languages or frameworks
Use this learning path to get hands-on practice with the essentials of DPC++ using Jupyter* Notebooks on Intel® DevCloud.
In addition to this training, the book, Data Parallel C++: Mastering DPC++ for Programming of Heterogeneous Systems Using C++ and SYCL, is now available.
Learn the fundamentals of using OpenMP* offload directives to target GPUs through hands-on practice in this guided learning path.
OpenMP* offload constructs are a set of directives for C++ and Fortran that allow you to offload data and execution to target accelerators such as GPUs. The constructs are supported in the Intel® oneAPI HPC Toolkit with the Intel® C++ Compiler and the Intel® Fortran Compiler.
Use this learning path to get hands-on practice with the essentials of DPC++ using Jupyter Notebooks on Intel® DevCloud.
Learn how the tool assists you in the migration of your CUDA* program to DPC++ via this self-guided, step-by-step tutorial.
The Intel® DPC++ Compatibility Tool assists you in migrating a CUDA* program to Data Parallel C++ (DPC++), which is based on modern C++ and incorporates portable industry standards such as SYCL*.
Get hands-on practice with the tool using this guided Jupyter Notebook on your local machine.
Learn how to use the Intel® OSPRay renderer and its API to create high-fidelity photorealistic images and scenes using simple geometries.
Intel® OSPRay is an open-source, scalable, and portable ray tracing engine for high-performance and scientific visualization applications. Effects such as ambient occlusion, shadows, and transparency can be rendered to enable new insight into huge data.
Use this learning path to get hands-on practice with the essentials of Intel® OSPRay using Jupyter Notebooks on Intel DevCloud.
Learn how to use the Intel® oneAPI Math Kernel Library (oneMKL) and its functions to create performant applications and speed up computations with low-level math routines.
The Intel® oneAPI Math Kernel Library enhances math routines such as vector and matrix operations from Basic Linear Algebra Subprograms (BLAS) and the Linear Algebra Package (LAPACK), fast Fourier transforms (FFT), and random number generator (RNG) functions.
Use this learning path to get hands-on practice with oneMKL using Jupyter Notebooks on Intel DevCloud.
Learn how to emulate FPGA hardware on the host, generate report files and optimize your design for the FPGA architecture, and compile and run your application on the FPGA fabric.
The Intel® FPGA Add-on for oneAPI Base Toolkit enables you to compile and run custom designs on FPGAs by generating bitstreams and configuring the hardware accelerator to meet the application's needs.
Use this learning path to get hands-on practice with the Intel® oneAPI Base Toolkit and Intel® FPGA Add-on for oneAPI Base Toolkit using Jupyter Notebooks on Intel DevCloud.
Preinstalled with the latest Intel hardware, frameworks, tools, and libraries, the Intel® DevCloud is a free service that enables you to get started without installing software locally. Sign up to gain access.
- Jupyter Notebook tutorials
- Basic shell commands
- Basic vi command
- Queue management and job submission
- Advanced queue management
Product and Performance Information
Performance varies by use, configuration and other factors. Learn more at www.Intel.com/PerformanceIndex.