2022-11-28 Fundamentals of Accelerated Computing with CUDA C,C++ (hdlw1w22)

Contents

The CUDA computing platform enables the acceleration of CPU-only applications to run on the world’s fastest massively parallel GPUs. In this course you experience C/C++ application acceleration by:

• Accelerating CPU-only applications to run their latent parallelism on GPUs

• Utilising essential CUDA memory management techniques to optimise accelerated applications

• Exposing accelerated application potential for concurrency and exploiting it with CUDA streams

• Leveraging command line and visual profiling to guide and check your work

Upon completion, you’ll be able to accelerate and optimise existing C/C++ CPU-only applications using the most essential CUDA tools and techniques. You’ll understand an iterative style of CUDA development that will allow you to ship accelerated applications fast.

The course is co-organised by LRZ, NHR@FAU and NVIDIA Deep Learning Institute (DLI). All instructors are NVIDIA certified University Ambassadors.

Important information

After you are accepted, please create an account under courses.nvidia.com/join .

Ensure your laptop / PC will run smoothly by going to http://websocketstest.com/ Make sure that WebSockets work for you by seeing under Environment, WebSockets is supported and Data Receive, Send and Echo Test all check Yes under WebSockets (Port 80).If there are issues with WebSockets, try updating your browser. If you have any questions, please contact Marjut Dieringer at mdieringer"at"nvidia.com. 

NVIDIA Deep Learning Institute

The NVIDIA Deep Learning Institute delivers hands-on training for developers, data scientists, and engineers. The program is designed to help you get started with training, optimising, and deploying neural networks to solve real-world problems across diverse industries such as self-driving cars, healthcare, online services, and robotics.

Prerequisites

Technical background, basic C/C++ programming skills.

Hands-On

The lectures are interleaved with many hands-on sessions using Jupyter Notebooks. The exercises will be done on a fully configured GPU-accelerated workstation in the cloud.

Language

English

Lecturer

Dr. Momme Allalen (LRZ and NVIDIA University Ambassador), Dr. Sebastian Kuckuk (NHR@FAU and NVIDIA University Ambassador)

Prices and Eligibility

The course is open and free of charge for people from academia from the Member States (MS) of the European Union (EU) and Associated Countries to the Horizon 2020 programme.

Registration

Please register with your official e-mail address to prove your affiliation.

Withdrawal Policy

See Withdrawal

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