HexiSeq optimizes sequence and head partitioning across mixed GPUs to improve long-context LLM training throughput by up to 1.72x in simulations.
Burstattention: An efficient distributed attention framework for extremely long sequences
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Belief2-Attention augments prior Belief-Attention with both projected and perpendicular signals plus an extra ZZ^T correlation matrix, claimed more expressive and tested on image classification and segmentation.
citing papers explorer
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HexiSeq: Accommodating Long Context Training of LLMs over Heterogeneous Hardware
HexiSeq optimizes sequence and head partitioning across mixed GPUs to improve long-context LLM training throughput by up to 1.72x in simulations.
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Improved Belief-Attention in Vision Task
Belief2-Attention augments prior Belief-Attention with both projected and perpendicular signals plus an extra ZZ^T correlation matrix, claimed more expressive and tested on image classification and segmentation.