196 citations · 823 across the 16 of their papers we have counts for
18 papers
Ultrafast jet classification on FPGAs for the HL-LHC
Patrick Odagiu, Zhiqiang Que, Javier Duarte +13
Three machine learning models are used to perform jet origin classification. These models are optimized for deployment on a field-programmable gate array device. In this context, w…
Ultra-low latency recurrent neural network inference on FPGAs for physics applications with hls4ml
Elham E Khoda, Dylan Rankin, Rafael Teixeira de Lima +10
Recurrent neural networks have been shown to be effective architectures for many tasks in high energy physics, and thus have been widely adopted. Their use in low-latency environme…
QONNX: Representing Arbitrary-Precision Quantized Neural Networks
Alessandro Pappalardo, Yaman Umuroglu, Michaela Blott +11
We present extensions to the Open Neural Network Exchange (ONNX) intermediate representation format to represent arbitrary-precision quantized neural networks. We first introduce s…
Real-time semantic segmentation on FPGAs for autonomous vehicles with hls4ml
Nicolò Ghielmetti, Vladimir Loncar, Maurizio Pierini +8
In this paper, we investigate how field programmable gate arrays can serve as hardware accelerators for real-time semantic segmentation tasks relevant for autonomous driving. Consi…
Lightweight Jet Reconstruction and Identification as an Object Detection Task
Adrian Alan Pol, Thea Aarrestad, Ekaterina Govorkova +8
We apply object detection techniques based on deep convolutional blocks to end-to-end jet identification and reconstruction tasks encountered at the CERN Large Hadron Collider (LHC…
Autoencoders on FPGAs for real-time, unsupervised new physics detection at 40 MHz at the Large Hadron Collider
Ekaterina Govorkova, Ema Puljak, Thea Aarrestad +11
In this paper, we show how to adapt and deploy anomaly detection algorithms based on deep autoencoders, for the unsupervised detection of new physics signatures in the extremely ch…