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tensor-parallelism

topic2 events
papersTODAY 04:00 UTC

Paper Proposes Affinity-Aware Sharding to Improve Delayed Tensor Parallelism

A new arXiv preprint examines Delayed Tensor Parallelism (DTP), a scheme that avoids the blocking all-reduce step in tensor-parallel Transformer inference by letting each device immediately add its partial output to the residual stream and broadcast it. The authors introduce affinity-aware sharding as a way to organize this communication and computation across devices. The work targets more efficient distributed inference for large Transformer models.

distributed-training/inference/transformers/arxiv
papersTODAY 04:00 UTC

X-Stage Paper Models Post-Issue Backpressure in Fused GPU Communication

A new arXiv paper examines how device-initiated communication affects fused GPU kernels that issue remote stores straight from their compute pipelines, a common pattern in expert and tensor parallelism. The authors introduce X-Stage, a model of post-issue backpressure that arises once such stores have been dispatched. The work aims to characterize performance limits in these communication-computation overlapped workloads.

gpu/distributed-training/arxiv/performance