A comprehensive survey on coded distributed computing: Fundamentals, challenges, and networking applications

JS Ng, WYB Lim, NC Luong, Z Xiong… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
Distributed computing has become a common approach for large-scale computation tasks
due to benefits such as high reliability, scalability, computation speed, and cost …

Short-dot: Computing large linear transforms distributedly using coded short dot products

S Dutta, V Cadambe, P Grover - Advances In Neural …, 2016 - proceedings.neurips.cc
Faced with saturation of Moore's law and increasing size and dimension of data, system
designers have increasingly resorted to parallel and distributed computing to reduce …

On the optimal recovery threshold of coded matrix multiplication

S Dutta, M Fahim, F Haddadpour… - IEEE Transactions …, 2019 - ieeexplore.ieee.org
We provide novel coded computation strategies for distributed matrix-matrix products that
outperform the recent “Polynomial code” constructions in recovery threshold, ie, the required …

Draco: Byzantine-resilient distributed training via redundant gradients

L Chen, H Wang, Z Charles… - … on Machine Learning, 2018 - proceedings.mlr.press
Distributed model training is vulnerable to byzantine system failures and adversarial
compute nodes, ie, nodes that use malicious updates to corrupt the global model stored at a …

Structural engineering from an inverse problems perspective

A Gallet, S Rigby, TN Tallman… - … of the Royal …, 2022 - royalsocietypublishing.org
The field of structural engineering is vast, spanning areas from the design of new
infrastructure to the assessment of existing infrastructure. From the onset, traditional entry …

Slow and stale gradients can win the race: Error-runtime trade-offs in distributed SGD

S Dutta, G Joshi, S Ghosh, P Dube… - International …, 2018 - proceedings.mlr.press
Abstract Distributed Stochastic Gradient Descent (SGD) when run in a synchronous manner,
suffers from delays in waiting for the slowest learners (stragglers). Asynchronous methods …

EEG emotion recognition using dynamical graph convolutional neural networks and broad learning system

X Wang, T Zhang, X Xu, L Chen, X Xing… - … on Bioinformatics and …, 2018 - ieeexplore.ieee.org
In recent years, electroencephalogram (EEG) e-motion recognition has been becoming an
emerging field in artificial intelligence area, which can reflect the relation between emotional …

Coded computing: Mitigating fundamental bottlenecks in large-scale distributed computing and machine learning

S Li, S Avestimehr - Foundations and Trends® in …, 2020 - nowpublishers.com
We introduce the concept of “coded computing”, a novel computing paradigm that utilizes
coding theory to effectively inject and leverage data/computation redundancy to mitigate …

A unified coded deep neural network training strategy based on generalized polydot codes

S Dutta, Z Bai, H Jeong, TM Low… - 2018 IEEE International …, 2018 - ieeexplore.ieee.org
This paper has two main contributions. First, we propose a novel coding technique-
Generalized PolyDot-for matrix-vector products that advances on existing techniques for …

Double coded caching in ultra dense networks: Caching and multicast scheduling via deep reinforcement learning

Z Zhang, H Chen, M Hua, C Li… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Proposed by Maddah-Ali and Niesen, a coded caching scheme has been verified to
alleviate the load of networks efficiently. Recently, a new technique called placement …