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UBDA Training Course: High Performance Computing with Python Workshop

Training Course

Poster-training_course_26_Sep_2022
  • Date

    21 Sep - 05 Oct 2022

  • Organiser

  • Time

    14:30 - 16:00

  • Venue

     

Summary

You are cordially invited to attend a training course spanning of 3 weeks. The course is focused on highly scalable parallel computing for helping research users to effectively use GPU and multiple processing resources on UBDA platform. It covers various topics from concepts of parallel computing, a suite of packages of RAPIDS – using the NVIDIA GPUs, cuDF, cuPy, and BlazingSQL, conducting analysis of bootstraps and machine learning with GPUs, Some Python programs and exercises will be conducted with Google Colaboratory. Also, demos will be illustrated of the use of the UBDA system. Participants are expected to have basic knowledge of Python. Please find the arrangements below

Course

 

High Performance Computing with Python Workshop (Poster)

Date

 

21 Sep 2022 to 5 Oct 2022

Venue   Online via Microsoft Teams

Session activities

 
  • Overview UBDA Services and Bootstraps (1st online session: 21 Sep 2022, 14:30 - 16:00)
  • Parallel Processing with RAPIDS (2nd online session: 28 Sep 2022, 14:30 - 16:00)
  • Machine Learning with GPU (3rd online session: 5 Oct 2022, 14:30 - 16:00)
Consultation Sessions  
  • 23 Sep 2022 (online/ P505, 11:00 – 12:00)
  • 30 Sep 2022 (online/ P505, 11:00 – 12:00)
  • 7 Oct 2022 (online/ P505, 11:00 – 12:00)

Registration / Quota  

 

PolyU staff and students
100 (first-come-first serve via online registration)
Confirmation emails will be sent to the registrants on 16 Sep 2022

Registration   https://www.polyu.edu.hk/pfs/index.php/914184?lang=en
Course Topics  
  • Overview UBDA Services and Bootstraps and Machine Learning with GPU
    • Introduction to UBDA Facility
    • Bootstrap basics
    • Bootstrap regression models
    • Bootstrap dependent data
  • Parallel Computing with RAPIDS
    • Introduction to Parallel and GPU Computing
    • RAPIDS – cuDF and cuPy
    • BlazingSQL
  • Machine Learning with GPU
    • cuML – Regression, Clustering
    • Dimensionality reduction

Should you have any enquiry, please contact Dr Vincent Ng at vincent.ng.comp@polyu.edu.hk and Dr Heung Wong at heung.wong@polyu.edu.hk or Dr Tarun Kulshrestha at tarun.kulshrestha@polyu.edu.hk

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