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Publications
Our publications provide insight into some of our leading-edge research.
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40 results found
Artificial Intelligence and Machine Learning
Computer Architecture
Clear all
Artificial Intelligence and Machine Learning
Computer Architecture
2018
UCNN: Exploiting Computational Reuse in Deep Neural Networks via Weight Repetition
Kartik Hegde, Jiyong Yu, Rohit Agrawal, Mengjia Yan,
Michael Pellauer
, Christopher W. Fletcher
Compressing DMA Engine: Leveraging Activation Sparsity for Training Deep Neural Networks
Minsoo Rhu,
Mike O'Connor
,
Niladrish Chatterjee
, Jeff Pool, Youngeun Kwon,
Steve Keckler
Stitch-X: An Accelerator Architecture for Exploiting Unstructured Sparsity in Deep Neural Networks
Ching-En Lee, Yakun Sophia Shao, Jie-Fang Zhang,
Angshuman Parashar
,
Joel Emer
,
Steve Keckler
, Zhengya Zhang
2017
Understanding Error Propagation in Deep Learning Neural Network (DNN) Accelerators and Applications
Guanpeng Li,
Siva Hari
,
Michael B. Sullivan
, Timothy Tsai, Karthik Pattabiraman,
Joel Emer
,
Steve Keckler
SCNN: An Accelerator for Compressed-sparse Convolutional Neural Networks
Angshuman Parashar
, Minsoo Rhu, Anurag Mukkara, Antonio Puglielli,
Rangharajan Venkatesan
,
Brucek Khailany
,
Joel Emer
,
Steve Keckler
,
William Dally
2016
vDNN: Virtualized Deep Neural Networks for Scalable, Memory-Efficient Neural Network Design.
Minsoo Rhu, Natalia Gimelshein,
Jason Clemons
, Arslan Zulfiqar,
Steve Keckler
Eyeriss: A Spatial Architecture for Energy-Efficient Dataflow for Convolutional Neural Networks
Yu-Hsin Chen,
Joel Emer
, Vivienne Sze
vDNN: Virtualized Deep Neural Networks for Scalable, Memory-Efficient Neural Network Design
Minsoo Rhu, Natalia Gimelshein,
Jason Clemons
, Arslan Zulfiqar,
Steve Keckler
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