ResearchTrend.AI
  • Papers
  • Communities
  • Organizations
  • 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. 1810.00307
  4. Cited By
Mini-batch Serialization: CNN Training with Inter-layer Data Reuse
v1v2v3v4 (latest)

Mini-batch Serialization: CNN Training with Inter-layer Data Reuse

30 September 2018
Sangkug Lym
Armand Behroozi
W. Wen
Ge Li
Yongkee Kwon
M. Erez
ArXiv (abs)PDFHTML

Papers citing "Mini-batch Serialization: CNN Training with Inter-layer Data Reuse"

11 / 11 papers shown
Title
BlockLLM: Multi-tenant Finer-grained Serving for Large Language Models
BlockLLM: Multi-tenant Finer-grained Serving for Large Language Models
Jiamin Li
Le Xu
Hong-Yu Xu
Aditya Akella
61
2
0
28 Apr 2024
SGCN: Exploiting Compressed-Sparse Features in Deep Graph Convolutional
  Network Accelerators
SGCN: Exploiting Compressed-Sparse Features in Deep Graph Convolutional Network Accelerators
Mingi Yoo
Jaeyong Song
Jounghoo Lee
Namhyung Kim
Youngsok Kim
Jinho Lee
GNN
97
22
0
25 Jan 2023
Slice-and-Forge: Making Better Use of Caches for Graph Convolutional
  Network Accelerators
Slice-and-Forge: Making Better Use of Caches for Graph Convolutional Network Accelerators
Min-hee Yoo
Jaeyong Song
Hyeyoon Lee
Jounghoo Lee
Namhyung Kim
Youngsok Kim
Jinho Lee
GNN
79
5
0
24 Jan 2023
EcoFlow: Efficient Convolutional Dataflows for Low-Power Neural Network
  Accelerators
EcoFlow: Efficient Convolutional Dataflows for Low-Power Neural Network Accelerators
Lois Orosa
Skanda Koppula
Yaman Umuroglu
Konstantinos Kanellopoulos
Juan Gómez Luna
Michaela Blott
K. Vissers
O. Mutlu
82
4
0
04 Feb 2022
Towards Memory-Efficient Neural Networks via Multi-Level in situ
  Generation
Towards Memory-Efficient Neural Networks via Multi-Level in situ Generation
Jiaqi Gu
Hanqing Zhu
Chenghao Feng
Mingjie Liu
Zixuan Jiang
Ray T. Chen
David Z. Pan
46
4
0
25 Aug 2021
Rethinking "Batch" in BatchNorm
Rethinking "Batch" in BatchNorm
Yuxin Wu
Justin Johnson
BDL
125
66
0
17 May 2021
Optimizer Fusion: Efficient Training with Better Locality and
  Parallelism
Optimizer Fusion: Efficient Training with Better Locality and Parallelism
Zixuan Jiang
Jiaqi Gu
Mingjie Liu
Keren Zhu
David Z. Pan
32
2
0
01 Apr 2021
GradPIM: A Practical Processing-in-DRAM Architecture for Gradient
  Descent
GradPIM: A Practical Processing-in-DRAM Architecture for Gradient Descent
Heesu Kim
Hanmin Park
Taehyun Kim
Kwanheum Cho
Eojin Lee
Soojung Ryu
Hyuk-Jae Lee
Kiyoung Choi
Jinho Lee
70
37
0
15 Feb 2021
FlexSA: Flexible Systolic Array Architecture for Efficient Pruned DNN
  Model Training
FlexSA: Flexible Systolic Array Architecture for Efficient Pruned DNN Model Training
Sangkug Lym
M. Erez
36
26
0
27 Apr 2020
Low-Memory Neural Network Training: A Technical Report
Low-Memory Neural Network Training: A Technical Report
N. Sohoni
Christopher R. Aberger
Megan Leszczynski
Jian Zhang
Christopher Ré
96
103
0
24 Apr 2019
PruneTrain: Fast Neural Network Training by Dynamic Sparse Model
  Reconfiguration
PruneTrain: Fast Neural Network Training by Dynamic Sparse Model Reconfiguration
Sangkug Lym
Esha Choukse
Siavash Zangeneh
W. Wen
Sujay Sanghavi
M. Erez
CVBM
85
88
0
26 Jan 2019
1