AgentServe: Algorithm-System Co-Design for Efficient Agentic AI Serving on a Consumer-Grade GPU
arXiv 2603.10342•a2fca645555d22a31fec85d45c3648d2c3800e4ad0f425e2cb4413541a5b08fb
AITERAMD InstinctCUDA Green ContextDGEMM emulationDMA orchestrationFP8GPU resource managementLLM servingOzaki‑IIRDMARaftRedFuserS‑HPLBTLA+ formalization','serverless anomaly detection','Hodge_decompagentic AIattention sparsityconsensus protocolscross‑domain latencydisaggregated inferencedmaplanehead‑parallelismhigh‑performance computinglatency stabilizationoperator fusionvLLM
Paper metadata
- arXiv ID
- 2603.10342
- 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
- a2fca645555d22a31fec85d45c3648d2c3800e4ad0f425e2cb4413541a5b08fb
- Enrichment time
- 2026-03-12T08:52:33Z
- AI-assisted enrichment
- Yes
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