6 February 2020
VŠB - Technical University Ostrava, IT4Innovations building
CET timezone
For academia only

Annotation

You learn the basics of OpenACC, a high-level programming language for programming on GPUs. Discover how to accelerate the performance of your applications beyond the limits of CPU-only programming with simple pragmas. You will learn:

  • How to profile and optimize your CPU-only applications to identify hot spots for acceleration
  • How to use OpenACC directives to GPU accelerate your codebase
  • How to optimize data movement between the CPU and GPU accelerator

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.

This training is a part of NVIDIA AI & HPC ACADEMY 2020.

The workshop is co-organized by LRZ, IT4Innovations and NVIDIA Deep Learning Institute (DLI) for the Partnership for Advanced Computing in Europe (PRACE). Both IT4Innovations and LRZ, as part of GCS, are PRACE Training Centres, serve as European hubs and key drivers of advanced high-quality training for researchers working in the computational sciences.

NVIDIA DLI offers hands-on training for developers, data scientists, and researchers looking to solve challenging problems with deep learning.

All instructors are NVIDIA certified University Ambassadors.

Level

Beginner

Language

English

Purpose of the course

Upon completion, you'll be ready to use OpenACC to GPU accelerate CPU-only applications.

About the tutor

Dr. Volker Weinberg studied physics at the Ludwig Maximilian University of Munich and later worked at the research centre DESY. He received his PhD from the Free University of Berlin for his studies in the field of lattice QCD. Since 2008 he is working in the HPC group at the Leibniz Supercomputing Centre and is education and training coordinator at LRZ. Volker is an NVIDIA Deep Learning Institute (DLI) certified OpenACC instructor participating in the University Ambassador program. Within PRACE, the Partnership for Advanced Computing in Europe, he is leading the workpackage WP5 "HPC Commissioning and Prototyping".

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, optimizing, and deploying neural networks to solve real-world problems across diverse industries such as self-driving cars, healthcare, online services, and robotics.

Acknowledgement

This event was partially supported by The Ministry of Education, Youth and Sports from the Large Infrastructures for Research, Experimental Development and Innovations project "e-Infrastruktura CZ – LM2018140“ and partially by the PRACE-6IP project - the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 823767. We would like to also thank Bayncore Labs for their contributions to this event.

 

Starts
Ends
CET
VŠB - Technical University Ostrava, IT4Innovations building
207
Studentská 6231/1B 708 33 Ostrava–Poruba Czech Republic

Practicalities

Prerequisities

After you are accepted, please create an account under courses.nvidia.com/join using the same email address as for event registration, since lab access is given based on the event registration list. Please be aware that for adminstrative reasons, after you register, Nvidia will use your email address to contact you for the final feedback of the workshop.

You must bring your own laptop to this workshop configured for wireless access.

Ensure your laptop 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.

Capacity and Fees

Capacity 30 participants.

The event is provided free of charge, including coffee breaks and lunches (cold snack).

Note, that this event is exclusively for verifiable students, staff, and researchers from any academic institution (for industrial participants, contact NVIDIA for industrial specific training). Please bring your student/academia id.

Accommodation and Transport recommendations

See the link above.

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Application
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