Minos: Systematically Classifying Performance and Power Characteristics of GPU Workloads on HPC Clusters
arXiv 2604.03591•a7f59d44a6edafbd7145d6f38779795dea0a3e197790812bf864412cc63a7197
autonomous-sreavailabilityblockchainconsensus-finalitydag-bftdiffusion-servingelasticsearchenergy-aware-schedulinggenservegpu-power-profilinghpcincident-responseledger-stigmergylemonsharkllm-tool-uselp-gemm','performance-optimization','memory-layout-propagation'minosnbi-slurmon-chain-coordinationperl-packagepreemptionslo-aware-schedulingslurmsupply-chain-risktelemetry-ingestion
Paper metadata
- arXiv ID
- 2604.03591
- 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
- a7f59d44a6edafbd7145d6f38779795dea0a3e197790812bf864412cc63a7197
- Enrichment time
- 2026-04-07T08:52:41Z
- AI-assisted enrichment
- Yes
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