VSC Training Course: Deep Learning and GPU programming using OpenACC, March 27-29, 2019

    Description:

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

    Learn how to train and deploy a neural network to solve real-world problems, how to generate effective descriptions of content within images and video clips and how to accelerate your applications with OpenACC.

    The workshop combines lectures about fundamentals of Deep Learning for Computer Vision and Multiple Data Types with a lecture about Accelerated Computing with 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 organized in cooperation with LRZ (Germany), IT4Innovations (Czech republic), and Nvidia. All instructors are NVIDIA certified University Ambassadors.

    Agenda:

    1st day, March 27, 2019: 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, March 28, 2019: Fundamentals of Deep Learning for Multiple Data Types

    This day explores how convolutional and recurrent neural networks can be combined to generate effective descriptions of content within images and video clips.

    Learn how to train a network using TensorFlow and the Microsoft Common Objects in Context (COCO) dataset to generate captions from images and video by:

    • Implementing deep learning workflows like image segmentation and text generation
    • Comparing and contrasting data types, workflows, and frameworks
    • Combining computer vision and natural language processing

    Upon completion, you’ll be able to solve deep learning problems that require multiple types of data inputs.

    3rd day, March 29, 2019: 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.

    Prerequisites:

    Technical background, basic understanding of machine learning concepts, basic C/C++ or Fortran programming skills.

    For the 1st day 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

    For the 2nd day familiarity with TensorFlow will be a plus as all the hands-on sessions are using TensorFlow. For those who do not program in TensorFlow, please go over TensorFlow tutorial (especially the "Learn and use ML" section): www.tensorflow.org/tutorials/

    Lecturers:

    Yu Wang (LRZ), Volker Weinberg (LRZ), Georg Zitzlsberger (IT4Innovations)

    Language:

    English

    Date, Time, and Location:

    Wednesday, March 27, 2019, 08:45: Registration and getting ready for the workshop
    27. - 29.03.2019, 09:00 - 17:00 (lunch breaks: 13:00-14:00, coffee breaks: 11:00-11:15 & 15:30-15:45),
    FH Internet-Raum FH1 (TU Wien, Wiedner Hauptstraße 8-10, ground floor, red area)

    Registration:

    Registration for this course is closed (fully booked).

    Registration deadline is Sunday, March 3, 2019, with priority rules. Acceptance will be approved on March 4, 2019. As long as seats are available there will be an extended registration period without priority rules.

    Priority for acceptance: first - active users of the VSC systems, second - students and members of Austrian universities and public research institutes, third - other academic applicants.

    Important Information: After you are accepted, please create an account under courses.nvidia.com/join using the same email address as for event registration.

    Hands-on sessions: Usually two participants will share one PC during the course. Participants may not claim one course PC for themselves. However, if you prefer to work on your own you may bring your own laptop with eduroam properly configured, the recommended browser for the course is a recent version of Chrome. Please ensure your laptop will run smoothly by going to 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.

    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.

    Local Organizer and Contact:

    Claudia Blaas-Schenner, vsc-seminar@list.tuwien.ac.at

     

    Training events (further courses) at:

    VSC: Opens external link in new windowvsc.ac.at/training

    LRZ: Opens external link in new windowwww.lrz.de/services/compute/courses/

    NVIDIA: Opens external link in new windowwww.nvidia.co.uk/dli