Adaptive Private Distributed Matrix Multiplication

01/14/2021
by   Rawad Bitar, et al.
0

We consider the problem of designing codes with flexible rate (referred to as rateless codes), for private distributed matrix-matrix multiplication. A master server owns two private matrices 𝐀 and 𝐁 and hires worker nodes to help computing their multiplication. The matrices should remain information-theoretically private from the workers. Codes with fixed rate require the master to assign tasks to the workers and then wait for a predetermined number of workers to finish their assigned tasks. The size of the tasks, hence the rate of the scheme, depends on the number of workers that the master waits for. We design a rateless private matrix-matrix multiplication scheme, called RPM3. In contrast to fixed-rate schemes, our scheme fixes the size of the tasks and allows the master to send multiple tasks to the workers. The master keeps sending tasks and receiving results until it can decode the multiplication; rendering the scheme flexible and adaptive to heterogeneous environments. Despite resulting in a smaller rate than known straggler-tolerant schemes, RPM3 provides a smaller mean waiting time of the master by leveraging the heterogeneity of the workers. The waiting time is studied under two different models for the workers' service time. We provide upper bounds for the mean waiting time under both models. In addition, we provide lower bounds on the mean waiting time under the worker-dependent fixed service time model.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
04/27/2020

Rateless Codes for Private Distributed Matrix-Matrix Multiplication

We consider the problem of designing rateless coded private distributed ...
research
08/12/2021

Secure Private and Adaptive Matrix Multiplication Beyond the Singleton Bound

Consider the problem of designing secure and private codes for distribut...
research
02/07/2018

Minimizing Latency for Secure Coded Computing Using Secret Sharing via Staircase Codes

We consider the setting of a Master server, M, who possesses confidentia...
research
09/01/2019

Private and Secure Distributed Matrix Multiplication with Flexible Communication Load

Large matrix multiplications are central to large-scale machine learning...
research
01/20/2020

Bivariate Polynomial Coding for Exploiting Stragglers in Heterogeneous Coded Computing Systems

Polynomial coding has been proposed as a solution to the straggler mitig...
research
06/27/2023

Sparse and Private Distributed Matrix Multiplication with Straggler Tolerance

This paper considers the problem of outsourcing the multiplication of tw...
research
01/23/2019

Distributed and Private Coded Matrix Computation with Flexible Communication Load

Tensor operations, such as matrix multiplication, are central to large-s...

Please sign up or login with your details

Forgot password? Click here to reset