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Running neural networks (NNs) on microcontroller units (MCUs) is becoming increasingly important, but is very difficult due to the tiny SRAM size of MCU.
Heap data allocation to scratch-pad memory in embedded systems
Angel Dominguez, Sumesh Udayakumaran, and Rajeev Barua · 2005
Earlier work this paper cites.
Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
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Deep learning with limited numerical precision
Suyog Gupta, Ankur Agrawal, Kailash Gopalakrishnan, and Pritish Narayanan · 2015
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Song Han, Huizi Mao, and William J Dally · 2015
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Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
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Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
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Hao Li, Asim Kadav, Igor Durdanovic, Hanan Samet, and Hans Peter Graf · 2016
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vdnn: Virtualized deep neural networks for scalable, memory-efficient neural network design
Minsoo Rhu, Natalia Gimelshein, Jason Clemons, Arslan Zulfiqar, and Stephen W Keckler · 2016
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All the aes you need on cortex-m3 and m4
Peter Schwabe and Ko Stoffelen · 2016
Earlier work this paper cites.
https://support.embeddedarm.com/support/solutions/articles/22000202867-reliable-sd-based-block-storage , 2017
Reliable sd-based block storage · 2017
Earlier work this paper cites.
Mobilenets: Efficient convolutional neural networks for mobile vision applications
Andrew G Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, and Hartwig Adam · 2017
Earlier work this paper cites.
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Haojin Yang, Martin Fritzsche, Christian Bartz, and Christoph Meinel · 2017
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Yundong Zhang, Naveen Suda, Liangzhen Lai, and Vikas Chandra · 2017
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Michael Zhu and Suyog Gupta · 2017
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https://csrc.nist.gov/csrc/media/events/lightweight-cryptography-workshop-2015/documents/presentations/session7-vincent.pdf , 2020
Performance of state-of-the-art cryptography on arm-based microprocessors · 2020
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https://en.wikipedia.org/wiki/STM32 , 2020
Stmicroelectronics stm32 family · 2020
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https://cdn.transcend-info.com/products/images/modelpic/574/EN_USDC10I_PS_2020.pdf , 2020
Transcend industrial temp microsd 64 gb · 2020
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Cmsis-nn: Efficient neural network kernels for arm cortex-m cpus
Liangzhen Lai, Naveen Suda, and Vikas Chandra · 2018
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Memory requirements for convolutional neural network hardware accelerators
Kevin Siu, Dylan Malone Stuart, Mostafa Mahmoud, and Andreas Moshovos · 2018
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Deeptype: On-device deep learning for input personalization service with minimal privacy concern
Mengwei Xu, Feng Qian, Qiaozhu Mei, Kang Huang, and Xuanzhe Liu · 2018
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Dynamic control flow in large-scale machine learning
Yuan Yu, Martín Abadi, Paul Barham, Eugene Brevdo, Mike Burrows, Andy Davis, Jeff Dean, Sanjay Ghemawat, Tim Harley, Peter Hawkins, et al · 2018
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Intelligence beyond the edge: Inference on intermittent embedded systems
Graham Gobieski, Brandon Lucia, and Nathan Beckmann · 2019
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Split-cnn: Splitting window-based operations in convolutional neural networks for memory system optimization
Tian Jin and Seokin Hong · 2019
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https://en.wikipedia.org/wiki/ARM_Cortex-M , 2020
Arm cortex-m · 2020
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Usb c power meter tester · 2020
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Tensorflow lite micro: Embedded machine learning on tinyml systems
Robert David, Jared Duke, Advait Jain, Vijay Janapa Reddi, Nat Jeffries, Jian Li, Nick Kreeger, Ian Nappier, Meghna Natraj, Shlomi Regev, et al · 2020
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What is the state of neural network pruning?
Jonathan Frankle John Guttag Davis Blalock, Jose Javier Gonzalez Ortiz · 2020
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Out-of-core training for extremely large-scale neural networks with adaptive window-based scheduling
Akio Hayakawa and Takuya Narihira · 2020
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Swapadvisor: Pushing deep learning beyond the gpu memory limit via smart swapping
Chien-Chin Huang, Gu Jin, and Jinyang Li · 2020
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Mcunet: Tiny deep learning on iot devices
Ji Lin, Wei-Ming Chen, Yujun Lin, John Cohn, Chuang Gan, and Song Han · 2020
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Approximate query service on autonomous iot cameras
Mengwei Xu, Xiwen Zhang, Yunxin Liu, Gang Huang, Xuanzhe Liu, and Felix Xiaozhu Lin · 2020
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Estimates of memory consumption and flop counts for various convolutional neural networks
Samuel albanie · 2021
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