Hierarchical Coding for Distributed Computing

TL;DR

This paper introduces a hierarchical coding scheme for distributed computing systems with a layered structure, improving decoding efficiency and reducing computation time compared to traditional non-hierarchical methods.

Contribution

It proposes a novel hierarchical coding scheme tailored for real-world distributed architectures and analyzes its decoding cost and expected computation time.

Findings

Hierarchical coding reduces decoding costs significantly.

The scheme outperforms existing methods in practical scenarios.

Bounds on expected computing time are established.

Abstract

Coding for distributed computing supports low-latency computation by relieving the burden of straggling workers. While most existing works assume a simple master-worker model, we consider a hierarchical computational structure consisting of groups of workers, motivated by the need to reflect the architectures of real-world distributed computing systems. In this work, we propose a hierarchical coding scheme for this model, as well as analyze its decoding cost and expected computation time. Specifically, we first provide upper and lower bounds on the expected computing time of the proposed scheme. We also show that our scheme enables efficient parallel decoding, thus reducing decoding costs by orders of magnitude over non-hierarchical schemes. When considering both decoding cost and computing time, the proposed hierarchical coding is shown to outperform existing schemes in many practical scenarios.