ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1909.07514
  4. Cited By
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

16 September 2019
Shihui Yin
Xiaoyu Sun
Shimeng Yu
Jae-sun Seo
    MQ
ArXivPDFHTML

Papers citing "High-Throughput In-Memory Computing for Binary Deep Neural Networks with Monolithically Integrated RRAM and 90nm CMOS"

10 / 10 papers shown
Title
Approximate ADCs for In-Memory Computing
Approximate ADCs for In-Memory Computing
Arkapravo Ghosh
Hemkar Reddy Sadana
Mukut Debnath
Panthadip Maji
Shubham Negi
Sumeet Gupta
M. Sharad
Kaushik Roy
21
0
0
11 Aug 2024
StoX-Net: Stochastic Processing of Partial Sums for Efficient In-Memory
  Computing DNN Accelerators
StoX-Net: Stochastic Processing of Partial Sums for Efficient In-Memory Computing DNN Accelerators
Ethan G Rogers
Sohan Salahuddin Mugdho
Kshemal Kshemendra Gupte
Cheng Wang
19
0
0
17 Jul 2024
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
O. Krestinskaya
Li Zhang
K. Salama
8
7
0
08 Jul 2023
Heterogeneous Integration of In-Memory Analog Computing Architectures
  with Tensor Processing Units
Heterogeneous Integration of In-Memory Analog Computing Architectures with Tensor Processing Units
Mohammed E. Elbtity
Brendan Reidy
Md Hasibul Amin
Ramtin Zand
26
5
0
18 Apr 2023
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
34
2
0
03 Jun 2022
Interconnect Parasitics and Partitioning in Fully-Analog In-Memory
  Computing Architectures
Interconnect Parasitics and Partitioning in Fully-Analog In-Memory Computing Architectures
Md Hasibul Amin
Mohammed E. Elbtity
Ramtin Zand
26
9
0
29 Jan 2022
An In-Memory Analog Computing Co-Processor for Energy-Efficient CNN
  Inference on Mobile Devices
An In-Memory Analog Computing Co-Processor for Energy-Efficient CNN Inference on Mobile Devices
Mohammed E. Elbtity
Abhishek Singh
Brendan Reidy
Xiaochen Guo
Ramtin Zand
15
17
0
24 May 2021
Mitigating Adversarial Attack for Compute-in-Memory Accelerator
  Utilizing On-chip Finetune
Mitigating Adversarial Attack for Compute-in-Memory Accelerator Utilizing On-chip Finetune
Shanshi Huang
Hongwu Jiang
Shimeng Yu
AAML
26
3
0
13 Apr 2021
Exploring the Connection Between Binary and Spiking Neural Networks
Exploring the Connection Between Binary and Spiking Neural Networks
Sen Lu
Abhronil Sengupta
MQ
14
101
0
24 Feb 2020
Google's Neural Machine Translation System: Bridging the Gap between
  Human and Machine Translation
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
Yonghui Wu
M. Schuster
Zhehuai Chen
Quoc V. Le
Mohammad Norouzi
...
Alex Rudnick
Oriol Vinyals
G. Corrado
Macduff Hughes
J. Dean
AIMat
718
6,750
0
26 Sep 2016
1