Intel® Artificial Intelligence Workshop: Enhance Machine Learning Performance with Intel® Software Tools

Date: Thursday, October 10, 2019, 9:00-12:30
Location: LRZ Building, Garching/Munich, Boltzmannstr. 1, LRZ Hörsaal
Contents:

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 workshop 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.

Schedule:

9:00 - 10:30

  • 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 Coffee break

11:00 - 12:30

  • Performance optimized Python
            Hands-on Labs with Python focus on Classical Machine Learning examples and algorithms
Prerequisites:

Basic knowledge of Python

Certificates of attendance for

All participants are expected to bring their own laptops.

Language: English
Contact:

F. Baruffa (Intel®), J. Albert-von der Gönna (LRZ)

Fabio Baruffa is a senior software technical consulting engineer at Intel. He provides customer support in the high performance computing (HPC) area and artificial intelligence software solutions at large scale. Prior to Intel, he has been working as HPC application specialist and developer in the largest supercomputing centers in Europe, mainly the Leibniz Supercomputing Centre and the Max-Plank Computing and Data Facility in Munich, as well as Cineca in Italy. He has been involved in software development, analysis of scientific code and optimization for HPC systems. He holds a PhD in Physics from University of Regensburg for his research in the area of spintronics devices and quantum computing.

Registration: Via the LRZ registration form. Please choose course HIML1W19.