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Ning Ge
Researcher at Tsinghua University
Publications - 346
Citations - 9705
Ning Ge is an academic researcher from Tsinghua University. The author has contributed to research in topics: Channel state information & Memristor. The author has an hindex of 33, co-authored 323 publications receiving 6549 citations. Previous affiliations of Ning Ge include Nanyang Technological University & Hewlett-Packard.
Papers
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Journal ArticleDOI
Memristors with diffusive dynamics as synaptic emulators for neuromorphic computing
Zhongrui Wang,Saumil Joshi,Sergey Savel'ev,Hao Jiang,Rivu Midya,Peng Lin,Miao Hu,Ning Ge,John Paul Strachan,Zhiyong Li,Qing Wu,Mark Barnell,Geng Lin Li,Huolin L. Xin,R. Stanley Williams,Qiangfei Xia,Jianhua Yang +16 more
TL;DR: The diffusive Ag-in-oxide memristor and its dynamics enable a direct emulation of both short- and long-term plasticity of biological synapses, representing an advance in hardware implementation of neuromorphic functionalities.
Journal ArticleDOI
Analogue signal and image processing with large memristor crossbars
Can Li,Miao Hu,Miao Hu,Yunning Li,Hao Jiang,Ning Ge,Eric Montgomery,Jiaming Zhang,Wenhao Song,Noraica Davila,Catherine Graves,Zhiyong Li,John Paul Strachan,Peng Lin,Zhongrui Wang,Mark Barnell,Qing Wu,R. Stanley Williams,Jianhua Yang,Qiangfei Xia +19 more
TL;DR: It is shown that reconfigurable memristor crossbars composed of hafnium oxide memristors on top of metal-oxide-semiconductor transistors are capable of analogue vector-matrix multiplication with array sizes of up to 128 × 64 cells.
Proceedings ArticleDOI
Dot-product engine for neuromorphic computing: programming 1T1M crossbar to accelerate matrix-vector multiplication
Miao Hu,John Paul Strachan,Zhiyong Li,Emmanuelle J. Merced Grafals,Noraica Davila,Catherine Graves,Si-Ty Lam,Ning Ge,Jianhua Yang,R. Stanley Williams +9 more
TL;DR: The Dot-Product Engine (DPE) is developed as a high density, high power efficiency accelerator for approximate matrix-vector multiplication, invented a conversion algorithm to map arbitrary matrix values appropriately to memristor conductances in a realistic crossbar array.
Journal ArticleDOI
Efficient and self-adaptive in-situ learning in multilayer memristor neural networks
Can Li,Daniel Belkin,Daniel Belkin,Yunning Li,Peng Yan,Peng Yan,Miao Hu,Miao Hu,Ning Ge,Hao Jiang,Eric Montgomery,Peng Lin,Zhongrui Wang,Wenhao Song,John Paul Strachan,Mark Barnell,Qing Wu,R. Stanley Williams,Jianhua Yang,Qiangfei Xia +19 more
TL;DR: This work monolithically integrate hafnium oxide-based memristors with a foundry-made transistor array into a multiple-layer memristor neural network and achieves competitive classification accuracy on a standard machine learning dataset.
Journal ArticleDOI
Memristor-Based Analog Computation and Neural Network Classification with a Dot Product Engine.
Miao Hu,Catherine Graves,Can Li,Yunning Li,Ning Ge,Eric Montgomery,Noraica Davila,Hao Jiang,R. Stanley Williams,Jianhua Yang,Qiangfei Xia,John Paul Strachan +11 more
TL;DR: High‐precision analog tuning and control of memristor cells across a 128 × 64 array is demonstrated, and the resulting vector matrix multiplication (VMM) computing precision is evaluated.