Distributed Approximate Computing with Constant Locality

Abstract

We 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 coding scheme. The scheme reduces the required rate by introducing auxiliary random variables and supports local decoding at the same time. Then we show the rate region is optimal under mild regularity conditions on source distributions. A coding for computing problem with side information is analogously studied. These results indicate that more rate has to be taken in order to achieve lower coding complexity in distributed computing settings. Moreover, useful graph characterizations are developed to simplify the computation of the achievable rate region.