Multi-user non-linearly separable distributed computing

Khalesi, Ali; Tanha, Ahmad; Malak, Derya; Elia, Petros

Submitted to ArXiV, 30 April 2026

This paper considers an

-server distributed computing setting with

users requesting functions that are arbitrary multivariable polynomial evaluations of

real (potentially non-linear) basis subfunctions, where each function output is raised to a bounded power. Our aim is to seek efficient task allocation and data communication techniques that reduce computation and communication costs. To this end, we take a tensor-theoretic approach, in which we represent the requested non-linearly decomposable functions using a properly designed tensor

, whose sparse decomposition into a tensor

and a matrix

directly defines the task assignment, connectivity, and communication patterns.

We design a lossless achievable scheme that integrates fixed-support SVD-based tensor factorization with multi-dimensional tiling of

and

, followed by a bipartite graph matching-based recursive assignment of tiles. This step transforms an overlapping decomposition into a disjoint one and reduces the resulting sum rank of the tiles, thereby decreasing the number of required servers. Under mild dimensionality conditions, we derive an explicit zero-error characterization of the achievable system rate

. Numerical simulations demonstrate the computational and communication savings over existing state-of-the-art matrix factorization approaches across a wide range of system parameters.

Detail

ARXIV

BIBTEX

Type:

Report

Date:

2026-04-30

Department:

Communication systems

Eurecom Ref:

8738

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