Block-Diagonal and LT Codes for Distributed Computing With Straggling Servers
Artikel i vetenskaplig tidskrift, 2019

We propose two coded schemes for the distributed computing problem of multiplying a matrix by a set of vectors. The first scheme is based on partitioning the matrix into submatrices and applying maximum distance separable (MDS) codes to each submatrix. For this scheme, we prove that up to a given number of partitions the communication load and the computational delay (not including the encoding and decoding delay) are identical to those of the scheme recently proposed by Li et al., based on a single, long MDS code. However, due to the use of shorter MDS codes, our scheme yields a significantly lower overall computational delay when the delay incurred by encoding and decoding is also considered. We further propose a second coded scheme based on Luby Transform (LT) codes under inactivation decoding. Interestingly, LT codes may reduce the delay over the partitioned scheme at the expense of an increased communication load. We also consider distributed computing under a deadline and show numerically that the proposed schemes outperform other schemes in the literature, with the LT code-based scheme yielding the best performance.

decoding delay

computational delay

distributed computing

Luby Transform codes

machine learning algorithms

maximum distance separable codes

Block-diagonal coding

straggling servers.


Albin Severinson

Simula UiB

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk, Kommunikationssystem

Alexandre Graell i Amat

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk, Kommunikationssystem

Eirik Rosnes

Simula UiB

IEEE Transactions on Communications

00906778 (ISSN)

Vol. 67 3 1739-1753 8502151

Distribuerad lagring för datalagring och trådlös leverans av data

Vetenskapsrådet (VR) (2016-04253), 2016-01-01 -- 2019-12-31.


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