A comprehensive survey on coded distributed computing: Fundamentals, challenges, and networking applications
Distributed computing has become a common approach for large-scale computation tasks
due to benefits such as high reliability, scalability, computation speed, and cost …
due to benefits such as high reliability, scalability, computation speed, and cost …
Short-dot: Computing large linear transforms distributedly using coded short dot products
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 …
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 …
outperform the recent “Polynomial code” constructions in recovery threshold, ie, the required …
Draco: Byzantine-resilient distributed training via redundant gradients
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 …
compute nodes, ie, nodes that use malicious updates to corrupt the global model stored at a …
Structural engineering from an inverse problems perspective
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 …
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
Abstract Distributed Stochastic Gradient Descent (SGD) when run in a synchronous manner,
suffers from delays in waiting for the slowest learners (stragglers). Asynchronous methods …
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
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 …
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 …
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
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 …
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
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 …
alleviate the load of networks efficiently. Recently, a new technique called placement …