GPU computing and its applications in High Energy Physics

Details of all lectures

Lecture 1 Theme: 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	Lecture 1	Introduction to parallel computing on GPUs	F elice Pantaleo
		Description 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.
		Pre-requisite Listeners don't need to have advanced knowledge about parallel computing or GPU programming

Lecture 2 Theme: GPU computing and its applications in High Energy Physics Lecture: Use of GPUs for triggering in HEP experiments *A few questions addressed in the lecture*
		Monday 25 February
11:30 12:25	Lecture 2	Use of GPUs for triggering in HEP experiments	F elice Pantaleo
		Description This lecture describes a pilot project for the use of GPUs in a real-time triggering application in the early trigger stages at the NA62 experiment at CERN, and the results of the first field tests together with a prototype data acquisition (DAQ) system. This pilot project within NA62 aims at integrating GPUs into the central L0 trigger processor, and also to use them as fast online processors for computing trigger primitives. The online use of GPUs would allow the computation of more complex trigger primitives already at this first trigger level.
		Audience and benefits This lecture targets physicists and engineers who are involved in the design of future triggering systems. After this lecture, the attendees are expected to have a good understanding of the reason why GPUs are considered a key technology for the development of a "software-based" triggering system.
		Pre-requisite knowledge and dependencies Participants having not attended lecture 1 may have difficulties to fully follow this lecture, if they are not somewhat familiar with GPU programming principles and abstractions.