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. 1902.10222
  4. Cited By
ROMANet: Fine-Grained Reuse-Driven Off-Chip Memory Access Management and
  Data Organization for Deep Neural Network Accelerators

ROMANet: Fine-Grained Reuse-Driven Off-Chip Memory Access Management and Data Organization for Deep Neural Network Accelerators

4 February 2019
Rachmad Vidya Wicaksana Putra
Muhammad Abdullah Hanif
Muhammad Shafique
ArXivPDFHTML

Papers citing "ROMANet: Fine-Grained Reuse-Driven Off-Chip Memory Access Management and Data Organization for Deep Neural Network Accelerators"

4 / 4 papers shown
Title
EnforceSNN: Enabling Resilient and Energy-Efficient Spiking Neural
  Network Inference considering Approximate DRAMs for Embedded Systems
EnforceSNN: Enabling Resilient and Energy-Efficient Spiking Neural Network Inference considering Approximate DRAMs for Embedded Systems
Rachmad Vidya Wicaksana Putra
Muhammad Abdullah Hanif
Muhammad Shafique
29
11
0
08 Apr 2023
Seculator: A Fast and Secure Neural Processing Unit
Seculator: A Fast and Secure Neural Processing Unit
Nivedita Shrivastava
S. Sarangi
AAML
18
3
0
19 Apr 2022
EF-Train: Enable Efficient On-device CNN Training on FPGA Through Data
  Reshaping for Online Adaptation or Personalization
EF-Train: Enable Efficient On-device CNN Training on FPGA Through Data Reshaping for Online Adaptation or Personalization
Yue Tang
Xinyi Zhang
Peipei Zhou
Jingtong Hu
13
17
0
18 Feb 2022
ReSpawn: Energy-Efficient Fault-Tolerance for Spiking Neural Networks
  considering Unreliable Memories
ReSpawn: Energy-Efficient Fault-Tolerance for Spiking Neural Networks considering Unreliable Memories
Rachmad Vidya Wicaksana Putra
Muhammad Abdullah Hanif
Muhammad Shafique
21
36
0
23 Aug 2021
1