Abstract

Synchronisation in the presence of noise and hardware performance variability is a key challenge that prevents applications from scaling to large problems and machines. Using asynchronous or semi-synchronous algorithms can help overcome this issue, but at the cost of reduced stability or convergence rate. In this paper we propose progressive load balancing to manage progress imbalance in asynchronous algorithms dynamically. In our technique the balancing is done over time, not instantaneously.Using Jacobi iterations as a test case, we show that, with CPU performance variability present, this approach leads to higher iteration rate and lower progress imbalance between parts of the solution space. We also show that under these conditions the balanced asynchronous method outperforms synchronous, semi-synchronous and totally asynchronous implementations in terms of time to solution.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call