Cover Image

TrackCore-F: Deploying Transformer-Based Subatomic Particle Tracking on FPGAs

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Blankestijn, Arjan, Odyurt, Uraz, Yousefzadeh, Amirreza
Format:	Preprint
Published:	2025
Subjects:	High Energy Physics - Experiment Hardware Architecture Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Ultra Fast Transformers on FPGAs for Particle Physics Experiments
by: Jiang, Zhixing, et al.
Published: (2024)

SparsePixels: Efficient Convolution for Sparse Data on FPGAs
by: Tsoi, Ho Fung, et al.
Published: (2025)

JEDI-linear: Fast and Efficient Graph Neural Networks for Jet Tagging on FPGAs
by: Que, Zhiqiang, et al.
Published: (2025)

Real-Time Stream Compaction for Sparse Machine Learning on FPGAs
by: Neu, Marc, et al.
Published: (2026)

TrackFormers: In Search of Transformer-Based Particle Tracking for the High-Luminosity LHC Era
by: Caron, Sascha, et al.
Published: (2024)

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware
by: Schulte, Jan-Frederik, et al.
Published: (2025)

AIE4ML: An End-to-End Framework for Compiling Neural Networks for the Next Generation of AMD AI Engines
by: Danopoulos, Dimitrios, et al.
Published: (2025)

HGQ-LUT: Fast LUT-Aware Training and Efficient Architectures for DNN Inference
by: Sun, Chang, et al.
Published: (2026)

da4ml: Distributed Arithmetic for Real-time Neural Networks on FPGAs
by: Sun, Chang, et al.
Published: (2025)

TrackFormers Part 2: Enhanced Transformer-Based Models for High-Energy Physics Track Reconstruction
by: Caron, Sascha, et al.
Published: (2025)

KANELÉ: Kolmogorov-Arnold Networks for Efficient LUT-based Evaluation
by: Hoang, Duc, et al.
Published: (2025)

Analysis of Hardware Synthesis Strategies for Machine Learning in Collider Trigger and Data Acquisition
by: Jia, Haoyi, et al.
Published: (2024)

Novel Approaches for ML-Assisted Particle Track Reconstruction and Hit Clustering
by: Odyurt, Uraz, et al.
Published: (2024)

Position: The Need for Ultrafast Training
by: Hoang, Duc
Published: (2026)

SoCks - Simplifying Firmware and Software Integration for Heterogeneous SoCs
by: Fuchs, Marvin, et al.
Published: (2025)

Shooting Neutrons at Neurons: Radiation Testing of a Spiking Neural Network on Flash-Based FPGAs
by: Nijsink, Wim, et al.
Published: (2026)

From RISC-V Cores to Neuromorphic Arrays: A Tutorial on Building Scalable Digital Neuromorphic Processors
by: Yousefzadeh, Amirreza
Published: (2025)

Reduced Simulations for High-Energy Physics, a Middle Ground for Data-Driven Physics Research
by: Odyurt, Uraz, et al.
Published: (2023)

Machine Learning on Heterogeneous, Edge, and Quantum Hardware for Particle Physics (ML-HEQUPP)
by: Gonski, Julia, et al.
Published: (2026)

Trikarenos: Design and Experimental Characterization of a Fault-Tolerant 28nm RISC-V-based SoC
by: Rogenmoser, Michael, et al.
Published: (2024)

Single Event Upsets characterization of 65 nm CMOS 6T and 8T SRAM cells for ground level environment
by: Malagon, Daniel, et al.
Published: (2024)

Data-Rate-Aware High-Speed CNN Inference on FPGAs
by: Habermann, Tobias, et al.
Published: (2026)

TinyFormer: Efficient Transformer Design and Deployment on Tiny Devices
by: Yang, Jianlei, et al.
Published: (2023)

A Runtime-Adaptive Transformer Neural Network Accelerator on FPGAs
by: Kabir, Ehsan, et al.
Published: (2024)

Enabling Long FFT Convolutions on Memory-Constrained FPGAs via Chunking
by: Wang, Peter, et al.
Published: (2025)

Dynamic Tsetlin Machine Accelerators for On-Chip Training at the Edge using FPGAs
by: Mao, Gang, et al.
Published: (2025)

FAMOUS: Flexible Accelerator for the Attention Mechanism of Transformer on UltraScale+ FPGAs
by: Kabir, Ehsan, et al.
Published: (2024)

TeLLMe: An Energy-Efficient Ternary LLM Accelerator for Prefilling and Decoding on Edge FPGAs
by: Qiao, Ye, et al.
Published: (2025)

H2PIPE: High throughput CNN Inference on FPGAs with High-Bandwidth Memory
by: Doumet, Mario, et al.
Published: (2024)

TsetlinWiSARD: On-Chip Training of Weightless Neural Networks using Tsetlin Automata on FPGAs
by: Duan, Shengyu, et al.
Published: (2026)

Efficient Message Passing Architecture for GCN Training on HBM-based FPGAs with Orthogonal Topology On-Chip Networks
by: Wu, Qizhe, et al.
Published: (2024)

HPCNeuroNet: A Neuromorphic Approach Merging SNN Temporal Dynamics with Transformer Attention for FPGA-based Particle Physics
by: Isik, Murat, et al.
Published: (2024)

TeLLMe v2: An Efficient End-to-End Ternary LLM Prefill and Decode Accelerator with Table-Lookup Matmul on Edge FPGAs
by: Qiao, Ye, et al.
Published: (2025)

Low latency optical-based mode tracking with machine learning deployed on FPGAs on a tokamak
by: Wei, Yumou, et al.
Published: (2023)

Explore Activation Sparsity in Recurrent LLMs for Energy-Efficient Neuromorphic Computing
by: Knunyants, Ivan, et al.
Published: (2025)

Runtime Tunable Tsetlin Machines for Edge Inference on eFPGAs
by: Rahman, Tousif, et al.
Published: (2025)

IMSSA: Deploying modern state-space models on memristive in-memory compute hardware
by: Siegel, Sebastian, et al.
Published: (2024)

Deeploy: Enabling Energy-Efficient Deployment of Small Language Models On Heterogeneous Microcontrollers
by: Scherer, Moritz, et al.
Published: (2024)

Rescaling-Aware Training for Efficient Deployment of Deep Learning Models on Full-Integer Hardware
by: Mueller, Lion, et al.
Published: (2025)

Toward Attention-based TinyML: A Heterogeneous Accelerated Architecture and Automated Deployment Flow
by: Wiese, Philip, et al.
Published: (2024)