Web: http://arxiv.org/abs/2201.11218

Jan. 28, 2022, 2:11 a.m. | Sheng-Chun Kao, Xiaoyu Huang, Tushar Krishna

cs.LG updates on arXiv.org arxiv.org

Dataflow/mapping decides the compute and energy efficiency of DNN
accelerators. Many mappers have been proposed to tackle the intra-layer
map-space. However, mappers for inter-layer map-space (aka layer-fusion
map-space), have been rarely discussed. In this work, we propose a mapper,
DNNFuser, specifically focusing on this layer-fusion map-space. While existing
SOTA DNN mapping explorations rely on search-based mappers, this is the first
work, to the best of our knowledge, to propose a one-shot inference-based
mapper. We leverage a famous language model GPT …

arxiv dnn accelerators fusion transformer

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