StageFrontier: Synchronization-Aware Stage Accounting for Distributed ML Training
arXiv 2606.06751•d428e9cd032cd913f8a3015665eb5045f68b4bcdbcda7ed855e0eafc3feefa9c
CPMLCUDADDPDxPTAFP8GPU-peer-to-peerGlooNCCLOzaki-IIPCCLPyTorchStageFrontiercollective-communicationdistributed-mlheterogeneous-acceleratorshigh-performance-computing (HPC)layer-variantsmulti-gpuobservabilityphotonic-acceleratorsprocess-groupsprofilingreal-time-dnnschedulingsynchronization
Paper metadata
- arXiv ID
- 2606.06751
- 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
- d428e9cd032cd913f8a3015665eb5045f68b4bcdbcda7ed855e0eafc3feefa9c
- Enrichment time
- 2026-06-08T08:52:27Z
- AI-assisted enrichment
- Yes
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