37 citations · 86 across the 16 of their papers we have counts for
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cs.AR2024★ 9 cited
FuseMax: Leveraging Extended Einsums to Optimize Attention Accelerator Design
Nandeeka Nayak, Xinrui Wu, Toluwanimi O. Odemuyiwa +3
Attention for transformers is a critical workload that has recently received significant "attention" as a target for custom acceleration. Yet, while prior work succeeds in reducing…
cs.LG2024
Characterizing the Accuracy -- Efficiency Trade-off of Low-rank Decomposition in Language Models
Chakshu Moar, Faraz Tahmasebi, Michael Pellauer +1
Recent large language models (LLMs) employ billions of parameters to enable broad problem-solving capabilities. Such language models also tend to be memory-bound because of the dom…