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GPU computing and its applications
in High Energy Physics
Details of all lectures
A few questions addressed
in the lecture |
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Monday
25 February |
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10:15 11:10 |
Lecture
1 |
Introduction
to parallel computing on GPUs |
Felice
Pantaleo
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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.
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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
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A few questions addressed
in the lecture |
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Monday
25 February |
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11:30 12:25 |
Lecture
2 |
Use of GPUs for triggering in HEP experiments |
Felice
Pantaleo
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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.
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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.
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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.
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