SiFAR: Synchronization-Free All-Reduce for Low-Latency LLM Inference
arXiv 2607.08973•e504ca089c62f4ad3e6219814c01ed2b528a64e3c2d990d2382891f829163004
AMD XDNAGPU computingKubernetesLLM inferenceNPU accelerationacademic researchall-reducearXivcarbon-aware schedulingdecentralized federated learningdistributed algorithmsdistributed systemsedge-cloud computingfederated learninggraph algorithmsperformance optimizationreinforcement learning
Paper metadata
- arXiv ID
- 2607.08973
- 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
- e504ca089c62f4ad3e6219814c01ed2b528a64e3c2d990d2382891f829163004
- Enrichment time
- 2026-08-16T13:05:41Z
- AI-assisted enrichment
- Yes
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