Paper Info
Title
An analytic computation-driven algorithm for Decentralized Multicore Systems.
Abstract
In the modern era, increasing numbers of cores per chip are applied for decentralized systems, but there is not any appropriate symbolic computation approach to construct multicore analytic approximation. Thus, it is essential to develop an efficient, simple and unified way for decentralized Adomian decomposition method to increase the potential speed of the multicore systems. In our paper, we present an innovative parallel algorithm of constructing analytic solutions for nonlinear differential system, which based on the Adomian–Rach double decomposition method and Rach’s Adomian polynomials. Based on our algorithm, we further developed a user-friendly Python software package to construct analytic approximations of initial or boundary value problems. Finally, the scope of validity of our Python software package is illustrated by several different types of nonlinear examples. The obtained results demonstrate the effectiveness of our package by compared with exact solution and numeric method, the characteristics of each class of Adomian polynomials and the efficiency of parallel algorithm with multicore processors. We emphasis that the super-linear speedup may happens for the duration of constructing approximate solutions. So, it can be considered as a promising alternative algorithm of decentralized Adomian decomposition method for solving nonlinear problems in science and engineering.
Year
DOI
Venue
2019
10.1016/j.future.2019.01.031
Future Generation Computer Systems
Keywords
Field
DocType
Parallel algorithm,Adomian–Rach double decomposition method,Adomian polynomials,Decentralized Multicore Systems
Nonlinear system,Parallel algorithm,Computer science,Symbolic computation,Algorithm,Decomposition method (constraint satisfaction),Adomian decomposition method,Python (programming language),Speedup,Computation
Journal
Volume
ISSN
Citations 
96
0167-739X
2
PageRank 
References 
Authors
0.40
0
5
Name
Order
Citations
PageRank
Yezhi Lin120.40
Xinyuan Jin220.74
Jiuqiang Chen320.40
Ali Hassan Sodhro411210.16
Zhifang Pan5493.51