# On Heterogeneous Coded Distributed Computing

arXiv: https://arxiv.org/abs/1709.00196 · HTML: https://mlsanity.com/paper/1709.00196/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Sep 2017.

## Built on by (most cited first, 1 of 1)

- [Optimization-based Block Coordinate Gradient Coding for Mitigating Partial Stragglers in Distributed Learning](https://mlsanity.com/paper/2206.02450/) (2022)

## Abstract (arXiv)

We consider the recently proposed Coded Distributed Computing (CDC) framework that leverages carefully designed redundant computations to enable coding opportunities that substantially reduce the communication load of distributed computing. We generalize this framework to heterogeneous systems where different nodes in the computing cluster can have different storage (or processing) capabilities. We provide the information-theoretically optimal data set placement and coded data shuffling scheme that minimizes the communication load in a cluster with 3 nodes. For clusters with K>3 nodes, we provide an algorithm description to generalize our coding ideas to larger networks.