mlsanityData to 7 Oct 2026

Ultra-low latency recurrent neural network inference on FPGAs for physics applications with hls4ml

arXiv 2207.00559 ↗First posted 1 Jul 2022cs.LG hep-ex physics.ins-detcited by 14

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Abstract (arXiv)

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 environments has, however, been limited as a result of the difficulties of implementing recurrent architectures on field-programmable gate arrays (FPGAs). In this paper we present an implementation of two types of recurrent neural network layers -- long short-term memory and gated recurrent unit -- within the hls4ml framework. We demonstrate that our implementation is capable of producing effective designs for both small and large models, and can be customized to meet specific design requirements for inference latencies and FPGA resources. We show the performance and synthesized designs for multiple neural networks, many of which are trained specifically for jet identification tasks at the CERN Large Hadron Collider.

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). Builds on 15 of its 42 references that are in the map. First posted on arXiv 1 Jul 2022.

Builds on

15 of 42 references.

References · 15

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2014Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translationcited by 4,016
  3. 2018Fast inference of deep neural networks in FPGAs for particle physicscited by 132
  4. 2020Compressing deep neural networks on FPGAs to binary and ternary precision with HLS4MLcited by 42
  5. 2021Fast convolutional neural networks on FPGAs with hls4mlcited by 42
  6. 2021A reconfigurable neural network ASIC for detector front-end data compression at the HL-LHCcited by 20
  7. 2017Long Short-Term Memory (LSTM) networks with jet constituents for boosted top tagging at the LHCcited by 13
  8. 2021Accelerating Recurrent Neural Networks for Gravitational Wave Experimentscited by 12
  9. 2018FINN-L: Library Extensions and Design Trade-off Analysis for Variable Precision LSTM Networks on FPGAscited by 10
  10. 2020FPGAs-as-a-Service Toolkit (FaaST)cited by 10
  11. 2015Recurrent Neural Networks Hardware Implementation on FPGAcited by 7
  12. 2018Jet Charge and Machine Learningcited by 5
3 more
  1. 2021Development of a Vertex Finding Algorithm using Recurrent Neural Networkcited by 4
  2. 2021Sequence-based Machine Learning Models in Jet Physicscited by 3
  3. 2016FPGA-Based Low-Power Speech Recognition with Recurrent Neural Networkscited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 2; 2024: 5; 2025: 5; 2026: 2.

14 papers.

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  1. 2025hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardwarecited by 8
  2. 2023On-Sensor Data Filtering using Neuromorphic Computing for High Energy Physics Experimentscited by 7
  3. 2023FPGA Resource-aware Structured Pruning for Real-Time Neural Networkscited by 7
  4. 2024Ultra Fast Transformers on FPGAs for Particle Physics Experimentscited by 6
  5. 2024Low Latency Transformer Inference on FPGAs for Physics Applications with hls4mlcited by 5
  6. 2024rule4ml: An Open-Source Tool for Resource Utilization and Latency Estimation for ML Models on FPGAcited by 3
  7. 2026JetFormer: A Scalable and Efficient Transformer for Jet Tagging from Offline Analysis to FPGA Triggerscited by 3
  8. 2025BitHEP -- The Limits of Low-Precision ML in HEPcited by 1
  9. 2024Scintillation pulse characterization with spectrum-inspired temporal neural networks: case studies on particle detector signalscited by 0
  10. 2024HPCNeuroNet: A Neuromorphic Approach Merging SNN Temporal Dynamics with Transformer Attention for FPGA-based Particle Physicscited by 0
  11. 2025FINN-GL: Generalized Mixed-Precision Extensions for FPGA-Accelerated LSTMscited by 0
  12. 2025Neural Network Acceleration on MPSoC board: Integrating SLAC's SNL, Rogue Software and Auto-SNLcited by 0
2 more
  1. 2025SparsePixels: Efficient Convolution for Sparse Data on FPGAscited by 0
  2. 2026Real-Time Plasma State Prediction via FPGA-Accelerated Quantized Recurrent Probabilistic Neural Networkscited by 0