Intel AI Workshop

Intel AI Workshop

Program

Enhance Machine Learning and Deep Learning Performance with Intel® Software tools

The use of data analytics techniques, such as Machine Learning and Deep Learning, has become the key for gaining insight into the incredible amount of data generated by scientific investigations (simulations and observations). Therefore, it is crucial for the scientific community to incorporate these new tools in their workflows, in order to make full use of modern and upcoming data sets. In this tutorial we will provide an overview on the most known machine learning algorithms for supervised and unsupervised learning. With small example codes we show how to implement such algorithms using the Intel® Distribution for Python*, and which performance benefit can be obtained with minimal effort from the developer perspective. Furthermore, the demand of using Deep Learning techniques in many scientific domains is rapidly emerging and the requirements for large compute and memory resources is increasing. One of the consequences is the need of the high-performance computing capability for processing and inferring the valuable information inherent in the data. We cover also how to accelerate the training of deep neural networks with Tensorflow, thanks to the highly optimized Intel® Math Kernel Library (Intel® MKL). We also demonstrate techniques on how to leverage deep neural network training on multiple nodes on an HPC system.

Registration

Registration is now open! Participation is free.

Please register via Indico conference management system in order to join the course, therefore you have to create a new account on Indico to register to the course “Intel AI Workshop”.

The registration is open until Monday, October 07th.

Please take into account, that the number of participants is limited. You will get a notification about the status of your registration.

Detailed information at Indico website: https://events.fias.science/.


Contact

Anja Gerbes, +49 (0)69 798-47356.

This course is organized by CSC, Goethe University Frankfurt in cooperation with

 

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Agenda

9:00 - 10:30 : Artificial Intelligence on Intel Hardware Platforms

  • Intel’s Hardware and Software directions for Artificial Intelligence (AI)

    • Machine Learning (ML) and Deep Learning (DL)

  • Hardware Accelerated Deep Learning instructions and implementations

    • DL Boost, VNNI instructions

10:30 – 11:00 Break

11:00 – 12:30 : Performance optimized Python

  • Hands-on Labs with Python focus on Classical Machine Learning examples and algorithms

12:30 – 14:00 Lunch Break

14:00 - 15:30 : Optimized Deep Learning Frameworks

  • Performance optimized Frameworks solutions from Intel

    • Tensorflow, Keras, Caffe, Pytorch, BigDL and others

  • Performance acceleration with Intel MKL and Intel MKL-DNN for Deep Neural Network

15:30 - 16:00 Break

16:00 - 17:00 : Distributed Deep Learning Solutions on HPC systems

  • Accelerate Training and Inference of Distributed solutions on HPC (MPI) environments using Xeon (x86)

    • Distributed Tensorflow with Horovod

    • Distributed Machine Learning with Daal4py