activity
20182021
most citedFast inference of deep neural networks in FPGAs for particle physics

438 citations · 851 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2021★ 8 cited

hls4ml: An Open-Source Codesign Workflow to Empower Scientific Low-Power Machine Learning Devices

Farah Fahim, Benjamin Hawks, Christian Herwig +27

Accessible machine learning algorithms, software, and diagnostic tools for energy-efficient devices and systems are extremely valuable across a broad range of application domains.…

cs.LG2021★ 131 cited

Fast convolutional neural networks on FPGAs with hls4ml

Thea Aarrestad, Vladimir Loncar, Nicolò Ghielmetti +17

We introduce an automated tool for deploying ultra low-latency, low-power deep neural networks with convolutional layers on FPGAs. By extending the hls4ml library, we demonstrate a…

physics.ins-det2020★ 32 cited

Accelerated Charged Particle Tracking with Graph Neural Networks on FPGAs

Aneesh Heintz, Vesal Razavimaleki, Javier Duarte +18

We develop and study FPGA implementations of algorithms for charged particle tracking based on graph neural networks. The two complementary FPGA designs are based on OpenCL, a fram…

physics.ins-det2020★ 50 cited

Distance-Weighted Graph Neural Networks on FPGAs for Real-Time Particle Reconstruction in High Energy Physics

Yutaro Iiyama, Gianluca Cerminara, Abhijay Gupta +19

Graph neural networks have been shown to achieve excellent performance for several crucial tasks in particle physics, such as charged particle tracking, jet tagging, and clustering…

cs.LG2020★ 114 cited

Compressing deep neural networks on FPGAs to binary and ternary precision with HLS4ML

Giuseppe Di Guglielmo, Javier Duarte, Philip Harris +13

We present the implementation of binary and ternary neural networks in the hls4ml library, designed to automatically convert deep neural network models to digital circuits with FPG…

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…

physics.ins-det2018★ 438 cited

Fast inference of deep neural networks in FPGAs for particle physics

Javier Duarte, Song Han, Philip Harris +8

Recent results at the Large Hadron Collider (LHC) have pointed to enhanced physics capabilities through the improvement of the real-time event processing techniques. Machine learni…