scholarly journals Graph neural network application to the particle track reconstruction for data from the GEM detector

2019 ◽  
Author(s):  
Dmitriy Baranov ◽  
Pavel Goncharov ◽  
Gennady Ososkov ◽  
Egor Shchavelev
2020 ◽  
Author(s):  
Megha Kolhekar ◽  
Ashish Pandey ◽  
Ayushi Raina ◽  
Rijin Thomas ◽  
Vaibhav Tiwari ◽  
...  

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Samuel Maddrell-Mander ◽  
Lakshan Ram Madhan Mohan ◽  
Alexander Marshall ◽  
Daniel O’Hanlon ◽  
Konstantinos Petridis ◽  
...  

AbstractThis paper presents the first study of Graphcore’s Intelligence Processing Unit (IPU) in the context of particle physics applications. The IPU is a new type of processor optimised for machine learning. Comparisons are made for neural-network-based event simulation, multiple-scattering correction, and flavour tagging, implemented on IPUs, GPUs and CPUs, using a variety of neural network architectures and hyperparameters. Additionally, a Kálmán filter for track reconstruction is implemented on IPUs and GPUs. The results indicate that IPUs hold considerable promise in addressing the rapidly increasing compute needs in particle physics.


1994 ◽  
Vol 26 (3) ◽  
pp. 23-29 ◽  
Author(s):  
Roman Erenshteyn ◽  
Richard Foulds ◽  
Scott Galuska

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