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

Workshop on Accelerating Scientific Applications using GPUs

April 19th - 23rd, 2020 (Event postponed due to COVID-19, stay tuned for updates)

Summary of agenda

  Events
Sun 19th Keynote, Introduction to OpenACC & Poster session
Mon 20th Keynote, Optimization with NVIDIA Nsight System & Nsight Compute
Tue 21st Hack-a-thon Day 1 (HPC stream), Introduction to RAPIDS for Deep Learning
Wed 22nd Hack-a-thon Day 2 (HPC stream), Hack-a-thon (AI Stream), Closing and awards ceremony for winners of hackathon

7th KAUST-NVIDIA Workshop

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 for Scientific Computing and Artificial Intelligence as well as showcasing the related KAUST success stories using GPUs.  

Hackathon

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.

AI competition

This year we are introducing an opportunity for those interested in developing Artificial Intelegence applications for analysing their scientific simulation big data. Domain specific curated 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. A prize will be awarded to the best performing model. 

Organizers

SaberFeki_1.2x1.jpg Saber Feki, Workshop Chair
bilel3.png Bilel Hadri, Workshop Co-Chair
Mohsin_A_Shaikh.png Mohsin Ahmed Shaikh, Workshop Co-Chair

Schedule

Day1

April, 19th, 2020.

Time: 9:00AM to 5:00PM

 Lecture Hall 2 room 2325 , bldg.9

Agenda: 

0900-1200

Training 1: Directive based GPU programming using OpenACC (Room XXXX, Bldg YY)

Dr. Saber Feki, Computatioal Science Team Lead, KAUST Supercomputing Core Lab

1200-1300

Keynote 1: NVIDIA (Auditorium 0215 BW Bldg 2&3)

1300-1400

Lunch + Poster Session (Auditorium 0215 BW Bldg 2&3)

1400-1700

Trainng 2: OpenACC, GPU Programming and Parallelware Tools

Dr. Manuel Arenaz, CEO at Appentra Solutions and professor of computer science, University of a Coruña, Spain

Keynote 1 speaker

Thimothy_Lanfear.png

Timothy Lanfear manages the European solution architecture and engineering team in NVIDIA’s Enterprise Solutions Group. He has twenty-five years’ experience in HPC, starting as a computational scientist in British Aerospace’s corporate research centre, and then moving to technical pre-sales roles with Hitachi, ClearSpeed, and most recently NVIDIA. He has a degree in Electrical Engineering and a PhD for research in the field of graph theory, both from Imperial College London. He is a Chartered Engineer and Member of the Institution of Engineering and Technology.

Abstract

  An Accelerated Computing System is Different
The title of the presentation is a quotation from Steve Oberlin, the CTO of NVIDIA’s accelerated computing business unit. An accelerated computing system should not be viewed as another type of computer to target for porting legacy applications, but rather a new computational platform enabling new approaches to simulation and modeling. This change was proven by the 2018 Gordon Bell Prize awards in which new algorithms and coupling AI methods with traditional simulation have advanced computational science. NVIDIA is innovating across all layers of the solution stack: the hardware and processor architecture; the programming model, libraries, tools, compilers, and new approaches to simulation.

Trainers

Dr. Saber Feki manages 

                Abstract

Directive based GPU programming using OpenACC

 

Dr. Manuel Arenaz is CEO at Appentra Solutions and professor of computer science at the University of A Coruña (Spain). Holds a PhD on advanced compiler techniques for automatic parallelization of scientific codes. After 10+ years teaching parallel programming at undergraduate and PhD levels, he strongly believes that the next generation of STEM engineers needs to be educated in HPC technologies to address the digital revolution challenge. Recently, he co-founded Appentra Solutions to commercialize products and services that take advantage of Parallware, a new technology for semantic analysis of scientific HPC codes. Parallware Trainer by Appentra is a step forward to enable experiential self-learning of parallel programming, one of the biggest technical challenges today. For this purpose, he led the foundation of the startup, conducted the technology transfer agreement and attended training courses for entrepreneur scientists. Now launching Parallelware Trainer to the HPC market.
Abstract OpenACC, GPU Programming and Parallelware Tools

Day2

April, 20th, 2020.

Time: 9:00AM to 5:00PM

Auditorium Room 0215 Bldg 4&5

Agenda: 

0900-1200

Profiling and debugging GPU applications using NVIDIA Nsight 

1200-1300 Keynote 2 (Auditorium Room 0215 Bldg 4&5)

1300-1400

Lunch

1400-1700

Profiling and debugging GPU applications using NVIDIA Nsight

Keynote 2 speaker

Speaker

Speaker Bio

Abstract

 Keynote 2

Trainers

Trainer

Trainer Bio

Abstract

Profiling and debugging GPU applications using NVIDIA Nsight

 

Hack-a-thon

The workshop will be followed by a two-day GPU hack-a-thon where 5-6 teams of developers will be selected to port and accelerate their domain science application to GPU accelerators. These teams will be guided by OpenACC and CUDA mentors from NVIDIA and KAUST.

Schedule:

        March 13-14, 2019

        Time: 9:00AM to 4:00PM

        Library, Computer Lab

Proposal: 

        Hack-a-thon proposal is free, limited to 5-6 teams, therefore please submit your proposal here.

Winners: 

        Nvidia will give Two GTX1080ti for winners

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
Other Matlab and GPU

Reference from last year: 

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

KAUST Map/Locations

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