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Found 3 papers, 2 papers with code
Trading Redundancy for Communication: Speeding up Distributed SGD for Non-convex Optimization
Communication overhead is one of the key challenges that hinder the scalability of distributed optimization algorithms to train large neural networks.
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, i. e., the required number of successful workers.
Information Theory Distributed, Parallel, and Cluster Computing Information Theory
Short-Dot: Computing Large Linear Transforms Distributedly Using Coded Short Dot Products
The fusion node can exploit this redundancy by completing the computation using outputs from only a subset of the processors, ignoring the stragglers.
