Local Decoding in Distributed Approximate Computing
Deheng Yuan, Tsinghua University, China; Tao Guo, Southeast University, China; Zhongyi Huang, Tsinghua University, China; Shi Jin, Southeast University, China
Session:
Coded and Distributed Computing
Track:
13: Coded or distributed computation
Location:
Omikron I
Presentation Time:
Thu, 11 Jul, 16:25 - 16:45
Session Chair:
Sihem Mesnager, Paris 8
Abstract
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.