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 …
Coded computation over heterogeneous clusters
In large-scale distributed computing clusters, such as Amazon EC2, there are several types
of “system noise” that can result in major degradation of performance: system failures …
of “system noise” that can result in major degradation of performance: system failures …
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 …
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 …
Stochastic gradient coding for straggler mitigation in distributed learning
R Bitar, M Wootters… - IEEE Journal on Selected …, 2020 - ieeexplore.ieee.org
We consider distributed gradient descent in the presence of stragglers. Recent work on
gradient coding and approximate gradient coding have shown how to add redundancy in …
gradient coding and approximate gradient coding have shown how to add redundancy in …
On the optimal recovery threshold of coded matrix multiplication
M Fahim, H Jeong, F Haddadpour… - 2017 55th Annual …, 2017 - 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 …
Coded distributed computing for inverse problems
Computationally intensive distributed and parallel computing is often bottlenecked by a
small set of slow workers known as stragglers. In this paper, we utilize the emerging idea …
small set of slow workers known as stragglers. In this paper, we utilize the emerging idea …
Minimizing latency for secure coded computing using secret sharing via staircase codes
We consider the setting of a Master server, M, who possesses confidential data and wants to
run intensive computations on it, as part of a machine learning algorithm for example. The …
run intensive computations on it, as part of a machine learning algorithm for example. The …
An application of storage-optimal matdot codes for coded matrix multiplication: Fast k-nearest neighbors estimation
We propose a novel application of coded computing to the problem of the nearest neighbor
estimation using MatDot Codes (Fahim et al., Allerton'17) that are known to be optimal for …
estimation using MatDot Codes (Fahim et al., Allerton'17) that are known to be optimal for …