Introduction to Machine Learning / TensorFlow (TBC) Room: Universite Catholique de Louvain <p>In most (scientific) machine learning applications,&nbsp;(deep) neural networks are employed&nbsp;due to their flexible and expressive nature.&nbsp;Among others,&nbsp;TensorFlow is a standard framework and software library to simplify, speed-up &nbsp;and improve the usage of neural networks. In this training session you will learn the basics of Neural Networks and how to train them using TensorFlow and Keras.</p> <table border="0" cellpadding="10px"> <tbody> <tr> <td rowspan="2"> <p><strong>Contents:</strong></p> <ul> <li>Basics of Neural Networks</li> <li>Basics of TensorFlow</li> <li>Keras API</li> <li>Examples</li> </ul> <p>&nbsp;</p> </td> <td> <p><strong>Prerequisite:</strong></p> <ul> <li>Being able to use SSH with private keys&nbsp;</li> <li>Being familiar with a text editor&nbsp;</li> <li>Mastering the Linux command line and the GNU utilities (mkdir, cp, scp, etc.)</li> <li>Basic knowledge of Python</li> </ul> <p><strong>Type:</strong>&nbsp;Hands-on<br /> <strong>Target audience</strong>: Rookie programmer<br /> <strong>Must:&nbsp;</strong>This session is nice-to-have for those who need or want&nbsp;to use&nbsp;neural networks.</p> </td> </tr> </tbody> </table>

HPC program portability

• Olivier Mattelaer (UCLouvain/CISM)

Room: Universite Catholique de Louvain <table border="0" cellpadding="10px"> <tbody> <tr> <td colspan="2"> <p>Singularity is a container solution for HPC. Containers help with reproducibility as they nicely package software and data dependencies, along with libraries that are needed. It allows users to install and run software that required root access to be installed on clusters where they only have regular user permissions. The rationale is to perform all the software installation in a container image (a kind of lightweight virtual machine, that can use a different Linux distribution than the one on the compute nodes!) on a machine where you have root access and then transfer and run that image on the machine on which you do not have root access. Images can be built from recipes shared by others, and from recipes made for Docker, the leader container solution outside the HPC world.</p> </td> </tr> <tr> <td rowspan="2"> <p><strong>Contents:</strong></p> <ul> <li>Container concepts and benefits</li> <li>Starting a Singularity container on the cluster</li> <li>Accessing the cluster filesystems</li> <li>Building a container image from a recipe</li> <li>Building a container image from scratch</li> <li>Singularity hub</li> </ul> </td> <td> <p><strong>Prerequisite:</strong></p> <ul> <li>Being able to use SSH with private keys&nbsp;</li> <li>Being familiar with a text editor&nbsp;</li> <li>Mastering the Linux command line and the GNU utilities (mkdir, cp, scp, etc.)</li> <li>Basic knowledge of Linux system administration</li> </ul> </td> </tr> <tr> <td> <p><br /> <strong>Type</strong>: Hands-on<br /> <strong>Target audience</strong>: Advanced user<br /> <strong>Must:&nbsp;</strong>This session is a must-have for anyone dealing with software that only installs on Ubuntu...</p> </td> </tr> </tbody> </table>

Introduction to BigData tools

• Michael Waumans (ULB)

Room: Universite Catholique de Louvain <table border="0" cellpadding="10px"> <tbody> <tr> <td colspan="2"> <p>High-performance compute and BigData are two disciplines that used to be higly compartmented, but are not anymore. More and more HPC users get interested in BigData software, and more and more BigData users get interested in HPC hardware. This session will broadly present the tools and concepts associated with BigData and explain how they can be used in the CÉCI context.</p> </td> </tr> <tr> <td rowspan="2"> <p><strong>Contents:</strong></p> <ul> <li>MapReduce and Spark</li> <li>Zeppelin and Jupyter</li> <li>BigData on HPC</li> </ul> </td> <td> <p><strong>Prerequisite:</strong></p> <ul> <li>Being able to use SSH with private keys&nbsp;</li> <li>Being familiar with a text editor&nbsp;</li> <li>Mastering the Linux command line and the GNU utilities (mkdir, cp, scp, etc.)</li> </ul> </td> </tr> <tr> <td> <p><strong>Type:</strong>&nbsp;Hands-on<br /> <strong>Target audience</strong>: Beginner<br /> <strong>Must:&nbsp;</strong>This session is a must-have for anyone who would like to go see what exist behind the buzzword.</p> </td> </tr> </tbody> </table>