POSTPONED: PRACE Course: Deep Learning and GPU Programming Workshop @ CSC Finland

Date:

Wednesday, April 22 - Friday, April 24, 2020, 9:00-17:00, CEST: POSTPONED

Location:

CSC – IT Center for Scienc, Life Science Center, Keilaranta 14, Espoo, Finland, training room Dogmi

More information on the venue and suggested hotels: https://www.csc.fi/en/web/guest/how-to-reach-us

Contents:

Due to COVID-19, the event will be POSTPONED! A new date will be announced as soon as the situation with COVID-19 is stabilised.

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Overview

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

The workshop combines lectures about fundamentals of Deep Learning for Computer Vision with lectures about Accelerated Computing with CUDA C/C++ and OpenACC.

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 workshop is co-organized by PRACE, Nvidia, CSC (Finland) and LRZ (Germany). All instructors are NVIDIA certified University Ambassadors.

Agenda

1st day: Fundamentals of Deep Learning for Computer Vision

Explore the fundamentals of deep learning by training neural networks and using results to improve performance and capabilities.

During this day, you’ll learn the basics of deep learning by training and deploying neural networks. You’ll learn how to:

  • Implement common deep learning workflows, such as image classification and object detection
  • Experiment with data, training parameters, network structure, and other strategies to increase performance and capability
  • Deploy your neural networks to start solving real-world problems

Upon completion, you’ll be able to start solving problems on your own with deep learning.

2nd day: Fundamentals of Accelerated Computing with CUDA C/C++

The CUDA computing platform enables the acceleration of CPU-only applications to run on the world’s fastest massively parallel GPUs. On the 2nd day you experience C/C++ application acceleration by:

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

  • Utilizing essential CUDA memory management techniques to optimize 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 optimize 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.

3rd day: Fundamentals of Accelerated Computing with OpenACC

On the 3rd day 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’ll 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

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

Important information

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. On the first day of the workshop, please also bring your student/academia ID.

For entering CSC's facilities, please show your identification with a photo at the LSCK reception to get your Visitor QR-badge. Your ID can be: a passport / driver licence / ID-card or a valid student card with a photo.

Course Fee

The workshop is free of charge for all academic participants and coffee breaks will be provided (lunch is not included). Please note, that the workshop is exclusively for verifiable students, staff, and researchers from any academic institution (for industrial participants, please contact NVIDIA for industrial specific training). On the first day of the workshop, please bring your student/academia id.

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.

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PRACE

Prerequisites:

Technical background, basic understanding of machine learning concepts, basic C/C++ or Fortran programming skills.
Basics in Python will be helpful. Since Python 2.7 is used, the following tutorial can be used to learn the syntax: docs.python.org/2.7/tutorial/index.html.

Content Level:

The content level of the course is broken down as:

Beginner's content: 5,9h 30%
Intermediate content: 13,7h 70%
Advanced content: 0,0h 0%
Community-targeted content: 0,0h 0%
Language: English
DLI Instructors: Dr. Momme Allalen, PD Dr. Juan Durillo Barrionuevo, Dr. Volker Weinberg (LRZ)
Registration: Via https://events.prace-ri.eu/event/998/
CSC Page: https://www.csc.fi/web/training/-/deep-learning-and-gpu-2020
Contact: Dr. Volker Weinberg (LRZ)