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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 …
Polynomial codes: an optimal design for high-dimensional coded matrix multiplication
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 …
out using a distributed system with a master node and multiple worker nodes, where each …
Speeding up distributed machine learning using codes
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 …
In large-scale systems, there are several types of noise that can affect the performance of …
Straggler mitigation in distributed matrix multiplication: Fundamental limits and optimal coding
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 …
analytic applications, in a large-scale distributed system comprising a group of worker …
A fundamental tradeoff between computation and communication in distributed computing
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 …
distributed computing? We answer this question by characterizing a fundamental tradeoff …
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
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 …
Coded sparse matrix multiplication
In a large-scale and distributed matrix multiplication problem $ C= A^{\intercal} B $, where $
C\in\mathbb {R}^{r\times t} $, the coded computation plays an important role to effectively …
C\in\mathbb {R}^{r\times t} $, the coded computation plays an important role to effectively …
Coded computing: Mitigating fundamental bottlenecks in large-scale distributed computing and machine learning
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 …