Neural networks on microcontrollers: saving memory at inference via operator reordering

2 October 2019

Papers citing "Neural networks on microcontrollers: saving memory at inference via operator reordering"

9 / 9 papers shown

Title
DTMM: Deploying TinyML Models on Extremely Weak IoT Devices with Pruning Lixiang Han Zhen Xiao Zhenjiang Li 41 5 0 17 Jan 2024
Pex: Memory-efficient Microcontroller Deep Learning through Partial Execution Edgar Liberis Nicholas D. Lane 13 3 0 30 Nov 2022
OLLA: Optimizing the Lifetime and Location of Arrays to Reduce the Memory Usage of Neural Networks Benoit Steiner Mostafa Elhoushi Jacob Kahn James Hegarty 29 8 0 24 Oct 2022
Demand Layering for Real-Time DNN Inference with Minimized Memory Usage Min-Zhi Ji Saehanseul Yi Chang-Mo Koo Sol Ahn Dongjoo Seo N. Dutt Jong-Chan Kim 42 16 0 08 Oct 2022
Design Automation for Fast, Lightweight, and Effective Deep Learning Models: A Survey Dalin Zhang Kaixuan Chen Yan Zhao B. Yang Li-Ping Yao Christian S. Jensen 43 3 0 22 Aug 2022
MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning Ji Lin Wei-Ming Chen Han Cai Chuang Gan Song Han 37 154 0 28 Oct 2021
Differentiable Network Pruning for Microcontrollers Edgar Liberis Nicholas D. Lane 22 18 0 15 Oct 2021
$μ$ NAS: Constrained Neural Architecture Search for Microcontrollers Edgar Liberis L. Dudziak Nicholas D. Lane BDL 13 103 0 27 Oct 2020
MCUNet: Tiny Deep Learning on IoT Devices Ji Lin Wei-Ming Chen Yujun Lin J. Cohn Chuang Gan Song Han 56 475 0 20 Jul 2020