specific method · filed under optimization
SM-Level Context Parallelism
A context-parallel method that partitions a sequence across the SMs of a single rank and combines segment transitions to recover exact initial states.
Also called intra-device context parallelism.
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Evidence
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An automatic SM-level context-parallel (CP) planner therefore partitions the sequence across the SMs of a single rank, evaluates the segment transitions in parallel, and merges them to recover each segment’s exact initial state.
usedunclearin Kimi K3Moonshot AI
Filed alongside
Other methods under optimization :: training parallelism.
Expert ParallelismTensor ParallelismMoonEPCommunication-Computation OverlapPipeline ParallelismAll-to-all Gradient Exchange with Local FP32 SummationCache-Based Pipeline CommunicationContext ParallelismData Replica Reduction over the Data Center NetworkData-Weighted Data ParallelismDynamic Context Parallelism for Large Multimodal SamplesFully Balanced Expert-Parallel TrainingGPU Planning Kernel for Redundant Expert MigrationHybrid ZeRO Bucket Assignment for MuonKDA Context ParallelismKnapsack-Based Balanced Assignment of Dense Parameter MatricesLoad-Balanced Image ShardingModified DualPipe 1F1B Pipeline Overlap for mHCNS-FLOP-Balanced Static Parameter PartitioningPipeline Payload ExtensionsPipeline ZeRO-2 Gradient Sharding with CPU Offloadingpipeline-bubble scheduling of ViT computationRedundant-Expert Capacity ReservationSConv-Aware Tensor-Parallel Sharding