Parallel simulations for Fractional-Order Systems

TL;DR

This paper demonstrates how parallel computing techniques, including GPU and HPC cluster implementations, can significantly accelerate numerical simulations of fractional-order systems, reducing computational costs over large time intervals.

Contribution

It introduces parallel algorithms for fractional-order system simulations and evaluates their efficiency using GPU and HPC cluster implementations.

Findings

Parallel algorithms achieve significant speedup.

GPU and HPC implementations are effective.

Computational costs are reduced for large time intervals.

Abstract

In this paper, we explore how numerical calculations can be accelerated by implementing several numerical methods of fractional-order systems using parallel computing techniques. We investigate the feasibility of parallel computing algorithms and their efficiency in reducing the computational costs over a large time interval. Particularly, we present the case of Adams-Bashforth-Mouhlton predictor-corrector method and measure the speedup of two parallel approaches by using GPU and HPC cluster implementations.