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null node-level-optimization-19
Node-level performance optimization
Date: 22.05.2019 9:00 - 24.05.2019 16:00
Location details: The event is organised at the CSC Training Facilities located in the premises of CSC at Keilaranta 14, Espoo, Finland. The best way to reach us is by public transportation; more detailed travel tips are available.
Language: english-language
lecturers: Sebastian von Alfthan (CSC)
Mikko Byckling (Intel)
Fredrik Robertsén (CSC)
Price:
  • free-price-finnish-academics.
  • free-price-others.
The fee covers all materials, lunches as well as morning and afternoon coffees.
registration-closed
The seats are filled in the registration order. If you have registered to this course and you are not able to attend, please CANCEL your registration in advance by sending an email to patc at csc.fi.
Additional Information
This course is part of the PRACE Training Centres (PTCs) activity. Please visit the PRACE Training portal for further information about the course. For content please contact sebastian.von.alfthan@csc.fi, for practicalities patc@csc.fi

Description

This course includes topics on code optimization for x86 platforms and efficient code parallelization on node-level using OpenMP threading. Advanced aspects of threading and optimization, such as selected topics of new features in OpenMP 5.0 standard, will be covered during the course.

Learning outcome

  • Awareness of modern features in x86 CPUs
  • Ability to vectorize computations
  • Ability to use advanced features of OpenMP
  • Ability to increase code performance using threading and x86 optimization

Prerequisites

  • Good knowledge of C/C++ or Fortran
  • Good knowledge of threading using OpenMP
  • Basic knowledge of modern CPU architectures

 

Program

Day1:

  • Course introduction and intro to CSC's new systems
  • Introduction to latest Intel(r) Xeon(r) Scalable Processor
  • Performance analysis methods and tools
  • Vectorization using SIMD

Day2:

  • OpenMP SIMD vectorization
  • Optimizing memory accesses

Day3:

  • Advanced OpenMP features
  • OpenMP performance considerations
  • Future outlook