Distributed Matrix Multiplication-Friendly Algebraic Function Fields
By: Yun Long Zhu, Chang-An Zhao
Potential Business Impact:
Makes computer math faster for certain tasks.
In this paper, we introduce distributed matrix multiplication (DMM)-friendly algebraic function fields for polynomial codes and Matdot codes, and present several constructions for such function fields through extensions of the rational function field. The primary challenge in extending polynomial codes and Matdot codes to algebraic function fields lies in constructing optimal decoding schemes. We establish optimal recovery thresholds for both polynomial algebraic geometry (AG) codes and Matdot AG codes for fixed matrix multiplication. Our proposed function fields support DMM with optimal recovery thresholds, while offering rational places that exceed the base finite field size in specific parameter regimes. Although these fields may not achieve optimal computational efficiency, our results provide practical improvements for matrix multiplication implementations. Explicit examples of applicable function fields are provided.
Similar Papers
Analog Secure Distributed Matrix Multiplication
Information Theory
Keeps secret math calculations safe from spies.
Optimal Secure Coded Distributed Computation over all Fields
Information Theory
Makes computer networks share data more safely.
Quantum Private Distributed Matrix Multiplication With Degree Tables
Information Theory
Makes private math calculations faster using quantum tricks.