DGNNFlow: A Streaming Dataflow Architecture for Real-Time Edge-based Dynamic GNN Inference in HL-LHC Trigger Systems
arXiv 2603.20364•bc76ad68158d979be52fb71edce453064e2f9811c036d4c8c3e1ef7b68ea33d5
AI-inferenceFPGAacademic-publicationcloud-computingdata-transferdistributed-systemsedge-computinggraph-neural-networkslarge-language-modelsmachine-learningmulti-cloudno-security-contentobservabilityresearchrobotics
Paper metadata
- arXiv ID
- 2603.20364
- Version
- Not specified by this published record
- Category
- Computer Science — Distributed, Parallel, and Cluster Computing (cs.DC)
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Evidence and limitations
- Source ID
- arxiv_cs_dc
- Record identifier
- bc76ad68158d979be52fb71edce453064e2f9811c036d4c8c3e1ef7b68ea33d5
- Enrichment time
- 2026-08-16T13:05:21Z
- AI-assisted enrichment
- Yes
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