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researcher

William J. Dally

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • last author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.AR1
  • cs.CL1
  • cs.CV1
  • cs.LG1
ORCID 0000-0003-4632-2876

identity via Semantic Scholar / OpenAlex

most citedTrained Ternary Quantization

746 citations · 950 across the 4 of their papers we have counts for

collaborators

4 papers

cs.AR2017

HoLiSwap: Reducing Wire Energy in L1 Caches

Yatish Turakhia, Subhasis Das, Tor M. Aamodt +1

This paper describes HoLiSwap a method to reduce L1 cache wire energy, a significant fraction of total cache energy, by swapping hot lines to the cache way nearest to the processor…

cs.LG2016★ 746 cited

Trained Ternary Quantization

Chenzhuo Zhu, Song Han, Huizi Mao +1

Deep neural networks are widely used in machine learning applications. However, the deployment of large neural networks models can be difficult to deploy on mobile devices with lim…

cs.CL2016★ 61 cited

ESE: Efficient Speech Recognition Engine with Sparse LSTM on FPGA

Song Han, Junlong Kang, Huizi Mao +9

Long Short-Term Memory (LSTM) is widely used in speech recognition. In order to achieve higher prediction accuracy, machine learning scientists have built larger and larger models.…

cs.CV2016★ 143 cited

DSD: Dense-Sparse-Dense Training for Deep Neural Networks

Song Han, Jeff Pool, Sharan Narang +9

Modern deep neural networks have a large number of parameters, making them very hard to train. We propose DSD, a dense-sparse-dense training flow, for regularizing deep neural netw…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.