TY - GEN

T1 - Codes for Distributed Finite Alphabet Matrix-Vector Multiplication

AU - Haddadpour, Farzin

AU - Cadambe, Viveck R.

N1 - Publisher Copyright:
© 2018 IEEE.
Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.

PY - 2018/8/15

Y1 - 2018/8/15

N2 - Recent work has developed coding theoretic approaches to add redundancy to distributed matrix-vector multiplications with the goal of speeding up the computation by mitigating the straggler effect in distributed computing. In this paper, we consider the case where the matrix comes from a small (e.g., binary) alphabet, where a variant of a popular method called the 'Four-Russians method' is known to have significantly lower computational complexity as compared with the usual matrix-vector multiplication algorithm. We develop novel code constructions that are applicable to binary matrix-vector multiplication via a variant of the Four-Russians method called the Mailman algorithm. Specifically, in our constructions, the encoded matrices have a low alphabet that ensures lower computational complexity, as well as good straggler tolerance. We also present a trade-off between the communication and computation cost of distributed coded matrix-vector multiplication for general, possibly non-binary, matrices.

AB - Recent work has developed coding theoretic approaches to add redundancy to distributed matrix-vector multiplications with the goal of speeding up the computation by mitigating the straggler effect in distributed computing. In this paper, we consider the case where the matrix comes from a small (e.g., binary) alphabet, where a variant of a popular method called the 'Four-Russians method' is known to have significantly lower computational complexity as compared with the usual matrix-vector multiplication algorithm. We develop novel code constructions that are applicable to binary matrix-vector multiplication via a variant of the Four-Russians method called the Mailman algorithm. Specifically, in our constructions, the encoded matrices have a low alphabet that ensures lower computational complexity, as well as good straggler tolerance. We also present a trade-off between the communication and computation cost of distributed coded matrix-vector multiplication for general, possibly non-binary, matrices.

UR - http://www.scopus.com/inward/record.url?scp=85052482857&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85052482857&partnerID=8YFLogxK

U2 - 10.1109/ISIT.2018.8437542

DO - 10.1109/ISIT.2018.8437542

M3 - Conference contribution

AN - SCOPUS:85052482857

SN - 9781538647806

T3 - IEEE International Symposium on Information Theory - Proceedings

SP - 1625

EP - 1629

BT - 2018 IEEE International Symposium on Information Theory, ISIT 2018

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2018 IEEE International Symposium on Information Theory, ISIT 2018

Y2 - 17 June 2018 through 22 June 2018

ER -