TY - GEN
T1 - Codes for Distributed Finite Alphabet Matrix-Vector Multiplication
AU - Haddadpour, Farzin
AU - Cadambe, Viveck R.
N1 - Publisher Copyright:
© 2018 IEEE.
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
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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 -