7th KAUST-NVIDIA Workshop on Accelerating Scientific Applications using GPUs

7th KAUST-NVIDIA Workshop on Accelerating Scientific Applications using GPUs

All sessions of this event will be hosted VIRTUALLY on Zoom. 

Date: November 23rd to December 10th, 2020 

The KAUST Supercomputing Core Laboratory (KSL) in collaboration with NVIDIA are pleased to invite you to the 7th annual workshop on "Accelerating Scientific Applications using GPUs". This event provides an opportunity for attendees to learn about the latest advances by NVIDIA in Scientific Computing and Artificial Intelligence as well as showcasing the related KAUST success stories using GPUs.  

 Organizers

Saber Feki.jpg Saber Feki, Workshop Chair
bilel3.png Bilel Hadri, HPC Hackathon Chair
Mohsin_A_Shaikh.png Mohsin Ahmed Shaikh, AI competition Chair

Hackathon

Registration form

Join us on Slack 

Dates: November 30th – December 2nd, 2020

As part of the workshop, we will be running 2 days of GPU hackathon where teams of developers will bring their own codes to either port to GPUs or optimize their pre-existing GPU codes on NVIDIA GPUs. Please see Call for Proposal for more details on how to participate. 
For participation please submit this registration form

AI competition

Registration form

Join us on Slack 

Dates: November 23rd – December 10th, 2020

This year we are introducing an opportunity for those interested in developing Artificial Intelegence applications for analysing their scientific simulation big data. Geospatial datasets along with a problem statement will be provided to the participants who will try and come up with a high performing Machine Learning/Deep Learning model. Prizes will be awarded to the best performing model. For details and registration please visit this PDF.

For beginners in Machine Learning and AI, we are running a separate event where the participants will have chance to train a regression model on a house pricing dateset. Some instructional resources along with a hands-on component has also been planned to give audience a background. 

Agenda

Note: For the events requiring registration, a confirmation email will be sent along with the link to the webinar. Please add this to your calendars for your convenience.

Date Time Sessions Registration Links
23/11 10:00 AM - 11:00 AM AI competition: Overview & Kick off Event link
24/11 1:00 PM - 3:30 PM Tutorial: Best Practices for Distributed Deep Learning on Ibex Register
25/11 9:30 AM - 12 PM Tutorial: Accelerated Data Science with NVIDIA RAPIDS Register
29/11 9:00 AM - 3:00 PM Tutorial: Directive based GPU programming using OpenACC Register
12:00 PM - 1:00 PM Tutorial: Overview of NVIDIA Nsight Systems Event link
30/11 12:00 PM - 12:30 PM (Formal) Opening of KAUST-NVIDIA Workshop On Accelerating Scientific Applications using GPUs Event link
HPC Hackathon: Overview & Kick off
12:30 PM - 1:30 PM Keynote:  A Universal Accelerated Computing Platform for the Data Centre (Dr. Timothy Lanfear, NVIDIA) 
2:00 PM - 3:00 PM Tutorial: Parallelware Analyzer -- Data race detection for GPUs using OpenMP and OpenACC Register
01/12 2:00 PM - 3:00 PM Tutorial: Overview of NVIDIA Nsight Compute Event link
02/12 9:00 AM - 12:00 PM Tutorial: Introduction to deep learning image classification using Keras (Part 1) Register
12:30 PM 13:30 PM Keynote: GPUs for HPC @ KAUST (Dr. Hatem Ltaief) Event link
3:30 PM - 4:30 PM HPC Hackathon: Team's presentations
5:00 PM HPC Hackathon: Prize ceremony & closing
03/12 09:00 AM - 10:30 AM Tutorial: Introduction to deep learning image classification using Keras (Part 2) -  Hands-on Use same link as in Part 1 (02/12/2020)
12 PM - 1 PM Keynote: AI in healthcare and lifescience (Craig Rhodes, NVIDIA) Event link
1:30 PM - 4:30PM ML competition: Predicting house pricing Use same link as in Part 1 (02/12/2020)
10/12 1:00 PM - 2:00 PM Keynote: AI@ KAUST (Prof. Brenard Ghanem)   Event link
2:00 PM - 3:30 PM AI competition: Prize ceremony and closing

Program details

Please visit here for details on all the events.

FAQs

You can read answers to Frequently Asked Qeustions here.

Reference Material

OpenACC OpenACC web page
OpenACC reference guide
OpenACC programming guide
OpenACC getting started guide
CUDA Cuda with C/C++
Cuda with Fortran
GPU Libraries GPUs libraries
Matlab for Deep Learning Matlab and GPU
ML with Scikit Learn

Part 1

Part 2

RAPIDS DLI Fundamentals of Accelerated Data Science with RAPIDS

Reference from last year:,GPU Hack-a-thon, 2018 materials: https://github.com/KAUST-KSL/GPUHACKATHON18

Follow us on Twitter @KAUST_HPC and please contact us at training@hpc.kaust.edu.sa if you need further information.