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Simba: Scaling Deep-Learning Inference with Multi-Chip-Module-Based Architecture
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Simba: Scaling Deep-Learning Inference with Multi-Chip-Module-Based Architecture

Shao, Yakun Sophia ; Clemons, Jason ; Venkatesan, Rangharajan ; Zimmer, Brian ; Fojtik, Matthew ; Jiang, Nan ; Keller, Ben ; Klinefelter, Alicia ; Pinckney, Nathaniel ; Raina, Priyanka ; Tell, Stephen G. ; Zhang, Yanqing ; Dally, William J. ; Emer, Joel ; Gray, C. Thomas ; Khailany, Brucek ; Keckler, Stephen W.

Proceedings of the 52nd Annual IEEE/ACM International Symposium on Microarchitecture, 2019, p.14-27

New York, NY, USA: ACM

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DaDianNao: A Machine-Learning Supercomputer
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DaDianNao: A Machine-Learning Supercomputer

Chen, Yunji ; Luo, Tao ; Liu, Shaoli ; Zhang, Shijin ; He, Liqiang ; Wang, Jia ; Li, Ling ; Chen, Tianshi ; Xu, Zhiwei ; Sun, Ninghui ; Temam, Olivier

2014 47th Annual IEEE/ACM International Symposium on Microarchitecture, 2014, p.609-622

Washington, DC, USA: IEEE Computer Society

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A dynamically configurable coprocessor for convolutional neural networks
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A dynamically configurable coprocessor for convolutional neural networks

Chakradhar, Srimat ; Sankaradas, Murugan ; Jakkula, Venkata ; Cadambi, Srihari

Proceedings of the 37th annual international symposium on Computer architecture, 2010, p.247-257

New York, NY, USA: ACM

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4
Transmuter: Bridging the Efficiency Gap using Memory and Dataflow Reconfiguration
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Transmuter: Bridging the Efficiency Gap using Memory and Dataflow Reconfiguration

Pal, Subhankar ; Feng, Siying ; Park, Dong-hyeon ; Kim, Sung ; Amarnath, Aporva ; Yang, Chi-Sheng ; He, Xin ; Beaumont, Jonathan ; May, Kyle ; Xiong, Yan ; Kaszyk, Kuba ; Morton, John Magnus ; Sun, Jiawen ; O'Boyle, Michael ; Cole, Murray ; Chakrabarti, Chaitali ; Blaauw, David ; Kim, Hun-Seok ; Mudge, Trevor ; Dreslinski, Ronald

Proceedings of the ACM International Conference on Parallel Architectures and Compilation Techniques, 2020, p.175-190

New York, NY, USA: ACM

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Pipelining a triggered processing element
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Pipelining a triggered processing element

Repetti, Thomas J. ; Cerqueira, João P. ; Kim, Martha A. ; Seok, Mingoo

2017 50th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO), 2017, p.96-108

New York, NY, USA: ACM

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6
TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning
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TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning

Kwon, Youngeun ; Lee, Yunjae ; Rhu, Minsoo

Proceedings of the 52nd Annual IEEE/ACM International Symposium on Microarchitecture, 2019, p.740-753

New York, NY, USA: ACM

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7
Towards General Purpose Acceleration by Exploiting Common Data-Dependence Forms
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Towards General Purpose Acceleration by Exploiting Common Data-Dependence Forms

Dadu, Vidushi ; Weng, Jian ; Liu, Sihao ; Nowatzki, Tony

Proceedings of the 52nd Annual IEEE/ACM International Symposium on Microarchitecture, 2019, p.924-939

New York, NY, USA: ACM

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8
SparTen: A Sparse Tensor Accelerator for Convolutional Neural Networks
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SparTen: A Sparse Tensor Accelerator for Convolutional Neural Networks

Gondimalla, Ashish ; Chesnut, Noah ; Thottethodi, Mithuna ; Vijaykumar, T. N.

Proceedings of the 52nd Annual IEEE/ACM International Symposium on Microarchitecture, 2019, p.151-165

New York, NY, USA: ACM

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The Unreasonable Effectiveness of Deep Features as a Perceptual Metric
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The Unreasonable Effectiveness of Deep Features as a Perceptual Metric

Zhang, Richard ; Isola, Phillip ; Efros, Alexei A. ; Shechtman, Eli ; Wang, Oliver

2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018, p.586-595

IEEE

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SNrram: an efficient sparse neural network computation architecture based on resistive random-access memory
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SNrram: an efficient sparse neural network computation architecture based on resistive random-access memory

Wang, Peiqi ; Ji, Yu ; Hong, Chi ; Lyu, Yongqiang ; Wang, Dongsheng ; Xie, Yuan

Proceedings of the 55th Annual Design Automation Conference, 2018, p.1-6

New York, NY, USA: ACM

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