Mixed-Precision Communication-Avoiding SGD for Generalized Linear Models on GPUs
arXiv 2606.18463•9b1d848a267090790dd946887b3c65414c8d3fd3e01f4095bddcb050706c9a2d
3D Gaussian SplattingAggregate ComputingEisenstein-Jacobi networksGPUsGaussian networks','model parallelism','runtime reconfigurationHPCIoTLLM servingPCIeRFSoCcommunication-avoiding SGDdistributed particle filteringdistributed systemsdistributed trainingfault tolerancefault-tolerant broadcastinggeneralized linear modelshardware interfaceheterogeneous GPU clustersmachine learningmixed-precisionmodel placementpixel-level communicationquantum controlspot instances
Paper metadata
- arXiv ID
- 2606.18463
- 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
- 9b1d848a267090790dd946887b3c65414c8d3fd3e01f4095bddcb050706c9a2d
- Enrichment time
- 2026-06-18T08:52:18Z
- AI-assisted enrichment
- Yes
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