The DOI matches its Crossref record; 50 of the 50 references it cites were found in a registry or an index.
On the Optimal Recovery Threshold of Coded Matrix Multiplication
Open accessAbstract
We provide novel coded computation strategies for distributed matrix-matrix products that outperform the recent “Polynomial code” constructions in recovery threshold, i.e., the required number of successful workers. When a fixed 1/m fraction of each matrix can be stored at each worker node, Polynomial codes require m2 successful workers, while our MatDot codes only require 2m - 1 successful workers. However, MatDot codes have higher computation cost per worker and higher communication cost from each worker to the fusion node. We also provide a systematic construction of MatDot codes. Furthermore, we propose “PolyDot” coding that interpolates between Polynomial codes and MatDot codes to trade off computation/communication costs and recovery thresholds. Finally, we demonstrate a novel coding technique for multiplying n matrices (n ≥ 3) using ideas from MatDot and PolyDot codes.
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Cites
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Speeding Up Distributed Machine Learning Using Codes
Lee, K., Lam, M., Pedarsani, R., Papailiopoulos, D., & Ramchandran, K. (2018) · IEEE Transactions on Information Theory · doi:10.1109/tit.2017.2736066 · Cited by 829
A Fundamental Tradeoff Between Computation and Communication in Distributed Computing
Li, S., Maddah-Ali, M. A., Yu, Q., & Avestimehr, A. S. (2018) · IEEE Transactions on Information Theory · doi:10.1109/tit.2017.2756959 · Cited by 451
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Polynomial Codes: an Optimal Design for High-Dimensional Coded Matrix Multiplication
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“Short-Dot”: Computing Large Linear Transforms Distributedly Using Coded Short Dot Products
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Self-citationCoded computation over heterogeneous clusters
Reisizadeh, A., Prakash, S., Pedarsani, R., & Avestimehr, S. (2017) · 2017 IEEE International Symposium on Information Theory (ISIT) · doi:10.1109/isit.2017.8006961 · Cited by 268
Cited by
Secure and Efficient Coded Multi-Access Edge Computing With Generalized Graph Neural Networks
Asheralieva, A., & Niyato, D. (2023) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2022.3172117 · Cited by 15
Metadata
- Authors
- Dutta, S., Fahim, M., Haddadpour, F., Jeong, H., Cadambe, V., & Grover, P.
- Venue
- IEEE Transactions on Information Theory
- Published
- 2020-01
- Volume
- 66
- Issue
- 1
- Pages
- 278-301
- ISSN
- 0018-9448 (ISSN-L)
- 1557-9654
- OpenAlex
- W2782956234
- Cited by
- 282
- References
- 50
- FWCI
- 22.86
- Type
- journal article
- Language
- en
- Open access
- green
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- Dutta, S., Fahim, M., Haddadpour, F., Jeong, H., Cadambe, V., & Grover, P. (2020). On the Optimal Recovery Threshold of Coded Matrix Multiplication. IEEE Transactions on Information Theory. https://doi.org/10.1109/tit.2019.2929328
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