Addressing Fluctuating Stragglers in Distributed Matrix Multiplication via Fountain Codes

In distributed matrix multiplication, stragglers present a significant challenge. Coding techniques are often employed to mitigate this issue; however, their effectiveness is typically limited to handling a fixed number of stragglers. To address the issue of a fluctuating number of stragglers, we propose a novel approach that leverages a variant of Luby transform (LT) codes for distributed matrix multiplication, augmented with a feedback mechanism. This enables the system to tolerate a variable number of stragglers, potentially reducing the redundant computation to complete the task compared with existing coding methods dealing with a fixed number of strangers. Furthermore, we comprehensively analyze the computational complexity associated with the proposed algorithm.

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Published
2024-11-24
DOI
https://doi.org/10.1109/itw61385.2024.10806990
Primary Topic
Error Correcting Code Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Addressing Fluctuating Stragglers in Distributed Matrix Multiplication via Fountain Codes

Linqi Song, Jianping Wang, Siyuan Wang
Error Correcting Code Techniques
article

Addressing Fluctuating Stragglers in Distributed Matrix Multiplication via Fountain Codes

Linqi Song, Jianping Wang, Siyuan Wang
article en

Abstract

In distributed matrix multiplication, stragglers present a significant challenge. Coding techniques are often employed to mitigate this issue; however, their effectiveness is typically limited to handling a fixed number of stragglers. To address the issue of a fluctuating number of stragglers, we propose a novel approach that leverages a variant of Luby transform (LT) codes for distributed matrix multiplication, augmented with a feedback mechanism. This enables the system to tolerate a variable number of stragglers, potentially reducing the redundant computation to complete the task compared with existing coding methods dealing with a fixed number of strangers. Furthermore, we comprehensively analyze the computational complexity associated with the proposed algorithm.

City University of Hong Kong (HK)
National Natural Science Foundation of China
Openalex Percentile: Top 72%
Error Correcting Code Techniques
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