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most citedFast inference of deep neural networks in FPGAs for particle physics

438 citations · 3.8k across the 51 of their papers we have counts for

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physics.comp-ph2022

Snowmass 2021 Computational Frontier CompF4 Topical Group Report: Storage and Processing Resource Access

W. Bhimji, D. Carder, E. Dart +17

Computing plays a significant role in all areas of high energy physics. The Snowmass 2021 CompF4 topical group's scope is facilities R&D, where we consider "facilities" as the comp…

physics.comp-ph2020★ 23 cited

FPGAs-as-a-Service Toolkit (FaaST)

Dylan Sheldon Rankin, Jeffrey Krupa, Philip Harris +13

Computing needs for high energy physics are already intensive and are expected to increase drastically in the coming years. In this context, heterogeneous computing, specifically a…

physics.comp-ph2020★ 26 cited

GPU-accelerated machine learning inference as a service for computing in neutrino experiments

Michael Wang, Tingjun Yang, Maria Acosta Flechas +7

Machine learning algorithms are becoming increasingly prevalent and performant in the reconstruction of events in accelerator-based neutrino experiments. These sophisticated algori…

physics.comp-ph2020

HL-LHC Computing Review: Common Tools and Community Software

HEP Software Foundation, :, Thea Aarrestad +107

Common and community software packages, such as ROOT, Geant4 and event generators have been a key part of the LHC's success so far and continued development and optimisation will b…

physics.comp-ph2020★ 17 cited

GPU coprocessors as a service for deep learning inference in high energy physics

Jeffrey Krupa, Kelvin Lin, Maria Acosta Flechas +13

In the next decade, the demands for computing in large scientific experiments are expected to grow tremendously. During the same time period, CPU performance increases will be limi…

physics.comp-ph2020★ 78 cited

Fast inference of Boosted Decision Trees in FPGAs for particle physics

Sioni Summers, Giuseppe Di Guglielmo, Javier Duarte +10

We describe the implementation of Boosted Decision Trees in the hls4ml library, which allows the translation of a trained model into FPGA firmware through an automated conversion p…