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.
|Saber Feki, Workshop Chair|
|Bilel Hadri, HPC Hackathon Chair|
|Mohsin Ahmed Shaikh, AI competition Chair|
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.
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.
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.
|23/11||10:00 AM - 11:00 AM||AI competition: Overview & Kick off||Event link||Recording/ Deck1/Deck2/Deck3|
|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||Slides/Video|
|29/11||9:00 AM - 3:00 PM||Tutorial: Directive based GPU programming using OpenACC||Register||Slides/Video|
|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||Keynote video|
|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||Video|
|01/12||2:00 PM - 3:00 PM||Tutorial: Overview of NVIDIA Nsight Compute||Event link||Slides/Video|
|02/12||9:00 AM - 12:00 PM||Tutorial: Introduction to deep learning image classification using Keras (Part 1)||Register||Video|
|12:30 PM 13:30 PM||Keynote: GPU-Accelerated Applications: The Why and The How? (Dr. Hatem Ltaief)||Event link||Keynote video|
|3:30 PM - 4:30 PM||HPC Hackathon: Team's presentations||Meeting Link|
|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)||Video|
|12 PM - 1 PM||Keynote: AI in healthcare and lifescience (Craig Rhodes, NVIDIA)||Event link||Keynote video|
|1:30 PM - 4:30PM||ML competition: Predicting house pricing||Use same link as in Part 1 (02/12/2020)||Slides|
|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|
Please visit here for details on all the events.
You can read answers to Frequently Asked Qeustions here.
|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|
|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