Wednesday 28 Nov 08:00

Workshop: Parallel Programming and Deep Learning

1 or 2 Day Course

FOOD: Yes

LEVEL: Intermediate

2 Days of deep-dive hands-on training sessions with Intel experts – bring your own laptop*!

Following a series of technical workshops on Parallel Programming and Deep Learning with Intel® Software, we are now going to the next level with the first hands-on workshop where you’ll have the opportunity to try all the software and programming techniques by yourself on your own laptop, guided by the experts.

Please bring your own – Intel®-based – laptop*, we’ll provide all required software and technology. Detailed technical requirements will be sent to the registered attendees.

REGISTER here There are seats left.

Date: 28 & 29 November 2018

AGENDA DAY 1**
08:00   09:00   Registration with light breakfast
09:00   19:00   Hands-on code training sessions on your own laptop PC

Lunch break at 12.00 and Coffee break at 15.00

PARALLELISM, PERFORMANCE & OPTIMIZATION ON INTEL® ARCHITECTURE – WHAT YOU SHOULD KNOW! (30 min)
The Intel® architecture offers parallelism at many different levels. Here we present the seven different levels of parallelism you should be thinking about when you write or optimize code.

SESSION 1: A STEP-BY-STEP APPROACH TO APPLICATION TUNING WITH INTEL® COMPILERS (3 hours)
In this first hands-on session, we follow the steps recommended by the Intel® Compiler Engineers that should be used to get the best performance out of the Intel® Compiler. Practical topics include general optimization, processor-specific options, inter procedural optimization, profile guided optimization, compiler optimization reports, and support for thread parallelism.

SESSION 2: HPC PERFORMANCE ANALYSIS USING INTEL® PARALLEL STUDIO (3 hours)
Starting from an un-optimized wave propagation kernel, we describe a general methodology to characterize and profile your code. We will see how threading, vectorization, but also memory optimization can affect the behaviour of your programs. The roofline model, dependency analysis, and memory access pattern analysis from Intel® Advisor as well as the HPC Performance Characterization and Memory Access from Intel® VTune™ Amplifier will be used to guide the developer to a more performant code. 

AT 17:30, PLEASE JOIN THE GET-TOGETHER NETWORKING EVENING WITH DRINKS & FOOD (1.5 hours)

AGENDA DAY 2**
08:00  09:00   Registration with light breakfast
09:00  17:00   Hands-on AI training sessions on your own laptop PC

Lunch break at 12.00 and Coffee break at 15.00

AI CONCEPTS (30 min)
In this session, we will explore the concepts and applications of Deep Learning, with a focus on real world applications using the Intel CPUs for training and inference.

HANDS-ON SESSION 1: GETTING STARTED ON INTEL® ARCHITECTURE (3 hours)
In this first session, we show how you can login to the two development environments and run some basic Intel® optimized Python* scripts. Firstly, using a VM image on your own laptop/pc, and secondly, working on the cloud using Intel® AI DevCloud.

HANDS-ON SESSION 2: INFERENCE ON THE EDGE USING THE INTEL® MOVIDIUS™ COMPUTE STICK (3 hours)
In this session, we discuss the advantages of using Caffe* optimized for Intel® Architecture and show how to train deep network models using one or more compute nodes. In the practical part of this session, you will then get chance to run a pre-trained model on the Intel® Movidius™ Neural Compute Stick.

MACHINE LEARNING IN THE LARGE (30 min)
Speed up your Spark*-based machine learning apps by using Intel® BigDL. In this session, we provide an overview of the BigDL library and a short demonstration of its usage within the Apache Spark ecosystem.

Date & Time:
Wednesday, November 28th
8.00 – 19.00 
Thursday, November 29th
9.15 – 17.00

Registration
You can register for both days or one of the days. 

REGISTER here There are seats left.

* Other names and brands may be claimed as the property of others.
** Agenda is subject to change
Preparation, configuration, and usage of your laptop computer during the workshop is at your own risk. Please note that Intel cannot take on any responsibility for your hardware.

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