Online Workshop on the new NVIDIA HPC SDK
The new NVIDIA HPC SDK significantly reshapes the diverse GPU metaprogramming approaches previously taken by OpenACC and Thrust/Bolt. With a new GPU-enabled std::par framework, a developer gets a vendor-neutral access to multicore CPUs and GPUs in a more unified fashion. In this webinar, we explain how to start using std::par in existing applications in typical software engineering scenarios. Furthermore, we focus on the new Nsight profiling tools, which are now free of a lot of limitations of the previous generation NVIDIA Visual Profiler. Finally, the webinar covers the new CUDA Fortran features as well as the Python bindings essential for any modern compute application. The online session will be accompanied by an optional offline practical hands-on, Q&A and submissions review. Attendees will have access to a JupyterLab environment with NVIDIA GPUs for the duration of the sessions. All corresponding presentations and code samples will be available to attendees as a downloadable package.
https://www.geophysik.uni-muenchen.de/en/seminars/seminars/geocomputing-28/online-workshop-on-the-new-nvidia-hpc-sdk
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Online Workshop on the new NVIDIA HPC SDK
Speaker
Dmitry Mikushin
(
Applied Parallel Computing LLC & Developers Source)
Abstract
The new NVIDIA HPC SDK significantly reshapes the diverse GPU metaprogramming approaches previously taken by OpenACC and Thrust/Bolt. With a new GPU-enabled std::par framework, a developer gets a vendor-neutral access to multicore CPUs and GPUs in a more unified fashion.
In this webinar, we explain how to start using std::par in existing applications in typical software engineering scenarios. Furthermore, we focus on the new Nsight profiling tools, which are now free of a lot of limitations of the previous generation NVIDIA Visual Profiler. Finally, the webinar covers the new CUDA Fortran features as well as the Python
bindings essential for any modern compute application. The online session will be accompanied by an optional offline practical hands-on, Q&A and submissions review. Attendees will
have access to a JupyterLab environment with NVIDIA GPUs for the duration of the sessions. All corresponding presentations and code samples will be available to attendees as a downloadable package.