6th  Inverted  CERN School of Computing 2013
25-26 February, CERN

Lecture 1

GPU computing and its applications in High Energy Physics

Lecture: Introduction to parallel computing on GPUs

A few questions addressed in the lecture

Monday  25 February


10:15 11:10


 Introduction to parallel computing on GPUs

Felice Pantaleo


All computing systems, from mobile to supercomputers, are becoming heterogeneous parallel computers using both multi-core CPUs and many-thread GPUs for higher power efficiency and computation throughput.
While the computing community is racing to build tools and libraries to ease the use of these heterogeneous parallel computing systems, effective and confident use of these systems will always require knowledge about the low-level programming interfaces in these systems.
This lecture is designed to introduce through examples, based on the CUDA programming language, the three abstractions that make the foundations of GPU programming:

- Thread hierarchy
- Synchronization
- Memory hierarchy/Shared Memory

The aim of this lecture is to give the audience a solid foundation on which to start building their own first GPU application.

Audience and benefits
This lecture targets physicists and engineers who are interested in improving the performance of their software by using off-the-shelf graphic car.

After this lecture, the attendees are expected to have a good understanding of the principles that govern parallel programming in CUDA and will be able to write their first GPU-accelerated application.

Listeners don't need to have advanced knowledge about parallel computing or GPU programming


  GPU computing and HEP  
Lecture 1
Lecture 2
  All lectures  
  Computer vision  
  Lecture 3  
  Lecture 4  
  Lecture 5  
  All lectures  
  Testing methods and tools  
Lecture 6
  Grid interpretation  
  Lecture 7  
  Programme overview  
  All lectures at iCSC2013  
  All questions addressed  


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