Local Decoding in Distributed Approximate Computing

Consider a distributed coding for computing problem with constant decoding locality, i.e., with a vanishing error probability, any single sample of the function can be approximately recovered by probing only constant number of compressed bits. We establish an achievable rate region by designing an e...

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Bibliographic Details
Published in:Proceedings / IEEE International Symposium on Information Theory pp. 2766 - 2771
Main Authors: Yuan, Deheng, Guo, Tao, Huang, Zhongyi, Jin, Shi
Format: Conference Proceeding
Language:English
Published: IEEE 07.07.2024
Subjects:
Approximate computing
Codes
Coding for computing
Decoding
distributed computing
Encoding
Error probability
graph characterization
Graph theory
local decoding
Random variables
ISSN:2157-8117
Online Access:Get full text
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Summary:Consider a distributed coding for computing problem with constant decoding locality, i.e., with a vanishing error probability, any single sample of the function can be approximately recovered by probing only constant number of compressed bits. We establish an achievable rate region by designing an efficient layered coding scheme, where the coding rate is reduced by introducing auxiliary random variables and local decoding is achieved by exploiting the expander graph code. Then we show the rate region is optimal under mild regularity conditions on source distributions. The proof relies on the reverse hypercontractivity and a rounding technique to construct auxiliary random variables. The rate region is strictly smaller than that for the classical problem without the constant locality constraint in most cases, which indicates that more rate is required in order to achieve lower coding complexity. Graph characterizations are also developed to simplify the computation of the achievable rate region.
ISSN:2157-8117
DOI:10.1109/ISIT57864.2024.10619658