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Towards Efficient In-memory Computing Hardware for Quantized Neural
  Networks: State-of-the-art, Open Challenges and Perspectives

Towards Efficient In-memory Computing Hardware for Quantized Neural Networks: State-of-the-art, Open Challenges and Perspectives

8 July 2023
O. Krestinskaya
Li Zhang
K. Salama
ArXivPDFHTML

Papers citing "Towards Efficient In-memory Computing Hardware for Quantized Neural Networks: State-of-the-art, Open Challenges and Perspectives"

16 / 16 papers shown
Title
A Co-design view of Compute in-Memory with Non-Volatile Elements for
  Neural Networks
A Co-design view of Compute in-Memory with Non-Volatile Elements for Neural Networks
W. Haensch
A. Raghunathan
Kaushik Roy
B. Chakrabarti
C. Phatak
Cheng Wang
Supratik Guha
44
2
0
03 Jun 2022
FAT: An In-Memory Accelerator with Fast Addition for Ternary Weight
  Neural Networks
FAT: An In-Memory Accelerator with Fast Addition for Ternary Weight Neural Networks
Shien Zhu
Luan H. K. Duong
Hui Chen
Di Liu
Weichen Liu
MQ
39
5
0
19 Jan 2022
SIAM: Chiplet-based Scalable In-Memory Acceleration with Mesh for Deep
  Neural Networks
SIAM: Chiplet-based Scalable In-Memory Acceleration with Mesh for Deep Neural Networks
Gokul Krishnan
Sumit K. Mandal
Manvitha Pannala
C. Chakrabarti
Jae-sun Seo
Ümit Y. Ogras
Yu Cao
40
41
0
14 Aug 2021
Layer-specific Optimization for Mixed Data Flow with Mixed Precision in
  FPGA Design for CNN-based Object Detectors
Layer-specific Optimization for Mixed Data Flow with Mixed Precision in FPGA Design for CNN-based Object Detectors
Duy-Thanh Nguyen
Hyun Kim
Hyuk-Jae Lee
MQ
27
60
0
03 Sep 2020
HMQ: Hardware Friendly Mixed Precision Quantization Block for CNNs
HMQ: Hardware Friendly Mixed Precision Quantization Block for CNNs
H. Habi
Roy H. Jennings
Arnon Netzer
MQ
45
65
0
20 Jul 2020
A Learning Framework for n-bit Quantized Neural Networks toward FPGAs
A Learning Framework for n-bit Quantized Neural Networks toward FPGAs
Jun Chen
Lu Liu
Yong Liu
Xianfang Zeng
MQ
58
26
0
06 Apr 2020
PANTHER: A Programmable Architecture for Neural Network Training
  Harnessing Energy-efficient ReRAM
PANTHER: A Programmable Architecture for Neural Network Training Harnessing Energy-efficient ReRAM
Aayush Ankit
I. E. Hajj
S. R. Chalamalasetti
S. Agarwal
M. Marinella
M. Foltin
J. Strachan
D. Milojicic
Wen-mei W. Hwu
Kaushik Roy
26
67
0
24 Dec 2019
Quantization Networks
Quantization Networks
Jiwei Yang
Xu Shen
Jun Xing
Xinmei Tian
Houqiang Li
Bing Deng
Jianqiang Huang
Xiansheng Hua
MQ
56
342
0
21 Nov 2019
High-Throughput In-Memory Computing for Binary Deep Neural Networks with
  Monolithically Integrated RRAM and 90nm CMOS
High-Throughput In-Memory Computing for Binary Deep Neural Networks with Monolithically Integrated RRAM and 90nm CMOS
Shihui Yin
Xiaoyu Sun
Shimeng Yu
Jae-sun Seo
MQ
24
105
0
16 Sep 2019
Additive Noise Annealing and Approximation Properties of Quantized
  Neural Networks
Additive Noise Annealing and Approximation Properties of Quantized Neural Networks
Matteo Spallanzani
Lukas Cavigelli
G. P. Leonardi
Marko Bertogna
Luca Benini
29
15
0
24 May 2019
Low-complexity Recurrent Neural Network-based Polar Decoder with Weight
  Quantization Mechanism
Low-complexity Recurrent Neural Network-based Polar Decoder with Weight Quantization Mechanism
Chieh-Fang Teng
Chengyang Wu
A. K. Ho
A. Wu
31
57
0
29 Oct 2018
ProxQuant: Quantized Neural Networks via Proximal Operators
ProxQuant: Quantized Neural Networks via Proximal Operators
Yu Bai
Yu Wang
Edo Liberty
MQ
45
117
0
01 Oct 2018
A Survey on Methods and Theories of Quantized Neural Networks
A Survey on Methods and Theories of Quantized Neural Networks
Yunhui Guo
MQ
54
232
0
13 Aug 2018
Restructuring Batch Normalization to Accelerate CNN Training
Restructuring Batch Normalization to Accelerate CNN Training
Wonkyung Jung
Daejin Jung
and Byeongho Kim
Sunjung Lee
Wonjong Rhee
Jung Ho Ahn
30
62
0
04 Jul 2018
BinaryConnect: Training Deep Neural Networks with binary weights during
  propagations
BinaryConnect: Training Deep Neural Networks with binary weights during propagations
Matthieu Courbariaux
Yoshua Bengio
J. David
MQ
142
2,976
0
02 Nov 2015
Compressing Deep Convolutional Networks using Vector Quantization
Compressing Deep Convolutional Networks using Vector Quantization
Yunchao Gong
Liu Liu
Ming Yang
Lubomir D. Bourdev
MQ
90
1,168
0
18 Dec 2014
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