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

JS Ng, WYB Lim, NC Luong, Z **ong… - … 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 …

Joint device scheduling and resource allocation for latency constrained wireless federated learning

W Shi, S Zhou, Z Niu, M Jiang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
In federated learning (FL), devices contribute to the global training by uploading their local
model updates via wireless channels. Due to limited computation and communication …

Speeding up distributed machine learning using codes

K Lee, M Lam, R Pedarsani… - IEEE Transactions …, 2017 - ieeexplore.ieee.org
Codes are widely used in many engineering applications to offer robustness against noise.
In large-scale systems, there are several types of noise that can affect the performance of …

Gradient coding: Avoiding stragglers in distributed learning

R Tandon, Q Lei, AG Dimakis… - … on Machine Learning, 2017 - proceedings.mlr.press
We propose a novel coding theoretic framework for mitigating stragglers in distributed
learning. We show how carefully replicating data blocks and coding across gradients can …

Polynomial codes: an optimal design for high-dimensional coded matrix multiplication

Q Yu, M Maddah-Ali… - Advances in Neural …, 2017 - proceedings.neurips.cc
We consider a large-scale matrix multiplication problem where the computation is carried
out using a distributed system with a master node and multiple worker nodes, where each …

A fundamental tradeoff between computation and communication in distributed computing

S Li, MA Maddah-Ali, Q Yu… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
How can we optimally trade extra computing power to reduce the communication load in
distributed computing? We answer this question by characterizing a fundamental tradeoff …

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 …

Straggler mitigation in distributed matrix multiplication: Fundamental limits and optimal coding

Q Yu, MA Maddah-Ali… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
We consider the problem of massive matrix multiplication, which underlies many data
analytic applications, in a large-scale distributed system comprising a group of worker …

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 …

High-dimensional coded matrix multiplication

K Lee, C Suh, K Ramchandran - 2017 IEEE International …, 2017 - ieeexplore.ieee.org
Coded computation is a framework for providing redundancy in distributed computing
systems to make them robust to slower nodes, or stragglers. In [1], the authors propose a …