Papers
Communities
Events
Blog
Pricing
Search
Open menu
Home
Papers
1803.01113
Cited By
Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in Distributed SGD
3 March 2018
Sanghamitra Dutta
Gauri Joshi
Soumyadip Ghosh
Parijat Dube
P. Nagpurkar
Re-assign community
ArXiv
PDF
HTML
Papers citing
"Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in Distributed SGD"
50 / 101 papers shown
Title
Orthogonal Calibration for Asynchronous Federated Learning
Jiayun Zhang
Shuheng Li
Haiyu Huang
Xiaofan Yu
Rajesh K. Gupta
Jingbo Shang
FedML
65
0
0
21 Feb 2025
ATA: Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning
A. Maranjyan
El Mehdi Saad
Peter Richtárik
Francesco Orabona
57
0
0
02 Feb 2025
Ringmaster ASGD: The First Asynchronous SGD with Optimal Time Complexity
A. Maranjyan
A. Tyurin
Peter Richtárik
42
2
0
28 Jan 2025
MindFlayer: Efficient Asynchronous Parallel SGD in the Presence of Heterogeneous and Random Worker Compute Times
A. Maranjyan
Omar Shaikh Omar
Peter Richtárik
28
3
0
05 Oct 2024
Faster Stochastic Optimization with Arbitrary Delays via Asynchronous Mini-Batching
Amit Attia
Ofir Gaash
Tomer Koren
40
0
0
14 Aug 2024
Finite-Time Analysis of Asynchronous Multi-Agent TD Learning
Nicolò Dal Fabbro
Arman Adibi
Aritra Mitra
George J. Pappas
42
1
0
29 Jul 2024
Ordered Momentum for Asynchronous SGD
Chang-Wei Shi
Yi-Rui Yang
Wu-Jun Li
ODL
59
0
0
27 Jul 2024
Distributed Stochastic Gradient Descent with Staleness: A Stochastic Delay Differential Equation Based Framework
Siyuan Yu
Wei Chen
H. V. Poor
32
0
0
17 Jun 2024
Buffered Asynchronous Secure Aggregation for Cross-Device Federated Learning
Kun Wang
Yi-Rui Yang
Wu-Jun Li
42
0
0
05 Jun 2024
ACCO: Accumulate While You Communicate for Communication-Overlapped Sharded LLM Training
Adel Nabli
Louis Fournier
Pierre Erbacher
Louis Serrano
Eugene Belilovsky
Edouard Oyallon
FedML
48
1
0
03 Jun 2024
FedAST: Federated Asynchronous Simultaneous Training
Baris Askin
Pranay Sharma
Carlee Joe-Wong
Gauri Joshi
49
2
0
01 Jun 2024
Communication-Efficient Distributed Deep Learning via Federated Dynamic Averaging
Michail Theologitis
Georgios Frangias
Georgios Anestis
V. Samoladas
Antonios Deligiannakis
FedML
40
0
0
31 May 2024
Dual-Delayed Asynchronous SGD for Arbitrarily Heterogeneous Data
Xiaolu Wang
Yuchang Sun
Hoi-To Wai
Jun Zhang
49
0
0
27 May 2024
Freya PAGE: First Optimal Time Complexity for Large-Scale Nonconvex Finite-Sum Optimization with Heterogeneous Asynchronous Computations
A. Tyurin
Kaja Gruntkowska
Peter Richtárik
44
3
0
24 May 2024
Asynchronous Federated Stochastic Optimization for Heterogeneous Objectives Under Arbitrary Delays
Charikleia Iakovidou
Kibaek Kim
FedML
35
2
0
16 May 2024
AntDT: A Self-Adaptive Distributed Training Framework for Leader and Straggler Nodes
Youshao Xiao
Lin Ju
Zhenglei Zhou
Siyuan Li
Zhaoxin Huan
...
Rujie Jiang
Lin Wang
Xiaolu Zhang
Lei Liang
Jun Zhou
34
1
0
15 Apr 2024
Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling
Arman Adibi
Nicolò Dal Fabbro
Luca Schenato
Sanjeev R. Kulkarni
H. Vincent Poor
George J. Pappas
Hamed Hassani
A. Mitra
35
8
0
19 Feb 2024
Achieving Linear Speedup in Asynchronous Federated Learning with Heterogeneous Clients
Xiaolu Wang
Zijian Li
Shi Jin
Jun Zhang
FedML
26
3
0
17 Feb 2024
Momentum Approximation in Asynchronous Private Federated Learning
Tao Yu
Congzheng Song
Jianyu Wang
Mona Chitnis
FedML
37
1
0
14 Feb 2024
CO2: Efficient Distributed Training with Full Communication-Computation Overlap
Weigao Sun
Zhen Qin
Weixuan Sun
Shidi Li
Dong Li
Xuyang Shen
Yu Qiao
Yiran Zhong
OffRL
61
10
0
29 Jan 2024
Ravnest: Decentralized Asynchronous Training on Heterogeneous Devices
A. Menon
Unnikrishnan Menon
Kailash Ahirwar
29
1
0
03 Jan 2024
DIGEST: Fast and Communication Efficient Decentralized Learning with Local Updates
Peyman Gholami
H. Seferoglu
FedML
18
11
0
14 Jul 2023
The Evolution of Distributed Systems for Graph Neural Networks and their Origin in Graph Processing and Deep Learning: A Survey
Jana Vatter
R. Mayer
Hans-Arno Jacobsen
GNN
AI4TS
AI4CE
48
23
0
23 May 2023
Taming Resource Heterogeneity In Distributed ML Training With Dynamic Batching
S. Tyagi
Prateek Sharma
24
22
0
20 May 2023
Fast and Straggler-Tolerant Distributed SGD with Reduced Computation Load
Maximilian Egger
Serge Kas Hanna
Rawad Bitar
FedML
24
0
0
17 Apr 2023
Gradient Descent with Linearly Correlated Noise: Theory and Applications to Differential Privacy
Anastasia Koloskova
Ryan McKenna
Zachary B. Charles
Keith Rush
Brendan McMahan
27
8
0
02 Feb 2023
ABS: Adaptive Bounded Staleness Converges Faster and Communicates Less
Qiao Tan
Feng Zhu
Jingjing Zhang
55
0
0
21 Jan 2023
Accelerating Parallel Stochastic Gradient Descent via Non-blocking Mini-batches
Haoze He
Parijat Dube
6
3
0
02 Nov 2022
Compute-Efficient Deep Learning: Algorithmic Trends and Opportunities
Brian Bartoldson
B. Kailkhura
Davis W. Blalock
31
47
0
13 Oct 2022
STSyn: Speeding Up Local SGD with Straggler-Tolerant Synchronization
Feng Zhu
Jingjing Zhang
Xin Wang
33
3
0
06 Oct 2022
Adaptive Stochastic Gradient Descent for Fast and Communication-Efficient Distributed Learning
Serge Kas Hanna
Rawad Bitar
Parimal Parag
Venkateswara Dasari
S. E. Rouayheb
30
2
0
04 Aug 2022
Sharper Convergence Guarantees for Asynchronous SGD for Distributed and Federated Learning
Anastasia Koloskova
Sebastian U. Stich
Martin Jaggi
FedML
30
78
0
16 Jun 2022
AsyncFedED: Asynchronous Federated Learning with Euclidean Distance based Adaptive Weight Aggregation
Qiyuan Wang
Qianqian Yang
Shibo He
Zhiguo Shi
Jiming Chen
FedML
37
25
0
27 May 2022
GBA: A Tuning-free Approach to Switch between Synchronous and Asynchronous Training for Recommendation Model
Wenbo Su
Yuanxing Zhang
Yufeng Cai
Kaixu Ren
Pengjie Wang
...
Jing Chen
Hongbo Deng
Jian Xu
Lin Qu
Bo Zheng
33
4
0
23 May 2022
CowClip: Reducing CTR Prediction Model Training Time from 12 hours to 10 minutes on 1 GPU
Zangwei Zheng
Peng Xu
Xuan Zou
Da Tang
Zhen Li
...
Xiangzhuo Ding
Fuzhao Xue
Ziheng Qing
Youlong Cheng
Yang You
VLM
44
7
0
13 Apr 2022
DeFTA: A Plug-and-Play Decentralized Replacement for FedAvg
Yuhao Zhou
M. Shi
Yuxin Tian
Qing Ye
Jiancheng Lv
FedML
19
2
0
06 Apr 2022
FLUTE: A Scalable, Extensible Framework for High-Performance Federated Learning Simulations
Mirian Hipolito Garcia
Andre Manoel
Daniel Madrigal Diaz
Fatemehsadat Mireshghallah
Robert Sim
Dimitrios Dimitriadis
FedML
27
57
0
25 Mar 2022
Towards Efficient and Stable K-Asynchronous Federated Learning with Unbounded Stale Gradients on Non-IID Data
Zihao Zhou
Yanan Li
Xuebin Ren
Shusen Yang
28
29
0
02 Mar 2022
Cost-Efficient Distributed Learning via Combinatorial Multi-Armed Bandits
Maximilian Egger
Rawad Bitar
Antonia Wachter-Zeh
Deniz Gunduz
FedML
24
2
0
16 Feb 2022
Asynchronous Decentralized Learning over Unreliable Wireless Networks
Eunjeong Jeong
Matteo Zecchin
Marios Kountouris
19
16
0
02 Feb 2022
Lightweight Projective Derivative Codes for Compressed Asynchronous Gradient Descent
Pedro Soto
Ilia Ilmer
Haibin Guan
Jun Li
32
3
0
31 Jan 2022
Privacy-Preserving Serverless Edge Learning with Decentralized Small Data
Shih-Chun Lin
Chia-Hung Lin
26
4
0
29 Nov 2021
DSAG: A mixed synchronous-asynchronous iterative method for straggler-resilient learning
A. Severinson
E. Rosnes
S. E. Rouayheb
Alexandre Graell i Amat
22
2
0
27 Nov 2021
Trade-offs of Local SGD at Scale: An Empirical Study
Jose Javier Gonzalez Ortiz
Jonathan Frankle
Michael G. Rabbat
Ari S. Morcos
Nicolas Ballas
FedML
43
19
0
15 Oct 2021
Distributed Optimization using Heterogeneous Compute Systems
S. Vineeth
30
0
0
03 Oct 2021
Coding for Straggler Mitigation in Federated Learning
Siddhartha Kumar
Reent Schlegel
E. Rosnes
Alexandre Graell i Amat
FedML
26
11
0
30 Sep 2021
On the Future of Cloud Engineering
David Bermbach
A. Chandra
C. Krintz
A. Gokhale
Aleksander Slominski
L. Thamsen
Everton Cavalcante
Tian Guo
Ivona Brandić
R. Wolski
43
23
0
19 Aug 2021
A Field Guide to Federated Optimization
Jianyu Wang
Zachary B. Charles
Zheng Xu
Gauri Joshi
H. B. McMahan
...
Mi Zhang
Tong Zhang
Chunxiang Zheng
Chen Zhu
Wennan Zhu
FedML
187
412
0
14 Jul 2021
Learning Under Delayed Feedback: Implicitly Adapting to Gradient Delays
R. Aviv
Ido Hakimi
Assaf Schuster
Kfir Y. Levy
38
9
0
23 Jun 2021
Federated Learning with Buffered Asynchronous Aggregation
John Nguyen
Kshitiz Malik
Hongyuan Zhan
Ashkan Yousefpour
Michael G. Rabbat
Mani Malek
Dzmitry Huba
FedML
33
288
0
11 Jun 2021
1
2
3
Next