Near-Optimal Fault Tolerance for Efficient Batch Matrix Multiplication via an Additive Combinatorics Lens

K Censor-Hillel, Y Machino, P Soto - International Colloquium on …, 2024 - Springer
Fault tolerance is a major concern in distributed computational settings. In the classic master-
worker setting, a server (the master) needs to perform some heavy computation which it may …

Random Alloy Codes and the Fundamental Limits of Coded Distributed Tensors

P Soto - 2024 IEEE Information Theory Workshop (ITW), 2024 - ieeexplore.ieee.org
Tensors are a fundamental operation in distributed computing, eg, machine learning, that
are commonly distributed into multiple parallel tasks for large datasets. Stragglers and other …

Algebraic Geometric Rook Codes for Coded Distributed Computing

GL Matthews, P Soto - arXiv preprint arXiv:2405.09746, 2024 - arxiv.org
We extend coded distributed computing over finite fields to allow the number of workers to
be larger than the field size. We give codes that work for fully general matrix multiplication …

Locally Random Alloy Codes with Channel Coding Theorems for Distributed Matrix Multiplication

P Soto, H Guan, J Li - arXiv preprint arXiv:2202.03469, 2022 - arxiv.org
Matrix multiplication is a fundamental operation in machine learning and is commonly
distributed into multiple parallel tasks for large datasets. Stragglers and other failures can …

Coded Distributed Function Computation

PJ Soto - 2022 - search.proquest.com
A ubiquitous problem in computer science research is the optimization of computation on
large data sets. Such computations are usually too large to be performed on one machine …