EPJ Web Conf.
Volume 245, 202024th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2019)
|Number of page(s)||7|
|Section||5 - Software Development|
|Published online||16 November 2020|
GPU Usage in ATLAS Reconstruction and Analysis
CERN, Geneva ; Switzerland
2 Lawrence Berkeley National Laboratory, Berkeley CA ; United States of America
3 University of California Irvine, Irvine CA ; United States of America
4 Brookhaven National Laboratory, Upton NY ; United States of America
* e-mail: Attila.Krasznahorkay@cern.ch
Published online: 16 November 2020
With Graphical Processing Units (GPUs) and other kinds of accelerators becoming ever more accessible, High Performance Computing Centres all around the world using them ever more, ATLAS has to find the best way of making use of such accelerators in much of its computing.
Tests with GPUs – mainly with CUDA – have been performed in the past in the experiment. At that time the conclusion was that it was not advantageous for the ATLAS offline and trigger software to invest time and money into GPUs. However as the usage of accelerators has become cheaper and simpler in recent years, their re-evaluation in ATLAS’s offline software is warranted.
We show new results of using GPU accelerated calculations in ATLAS’s offline software environment using the ATLAS offline/analysis (xAOD) Event Data Model. We compare the performance and flexibility of a couple of the available GPU programming methods, and show how different memory management setups affect our ability to offload different types of calculations to a GPU efficiently.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.