Partitioning techniques and their parallelization for stiff system of ordinary differential equations

A new code based on variable order and variable stepsize component wise partitioning is introduced to solve a system of equations dynamically. In previous partitioning technique researches, once an equation is identified as stiff, it will remain in stiff subsystem until the integration is complet...

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Main Author: Othman, Khairil Iskandar
Format: Thesis
Language:English
English
Published: 2007
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Online Access:http://psasir.upm.edu.my/id/eprint/8531/1/FS_2007_39_IR.pdf
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spelling my-upm-ir.85312023-12-06T00:28:47Z Partitioning techniques and their parallelization for stiff system of ordinary differential equations 2007-04 Othman, Khairil Iskandar A new code based on variable order and variable stepsize component wise partitioning is introduced to solve a system of equations dynamically. In previous partitioning technique researches, once an equation is identified as stiff, it will remain in stiff subsystem until the integration is completed. In this current technique, the system is treated as nonstiff and any equation that caused stiffness will be treated as stiff equation. However, should the characteristics showed the elements of nonstiffness, and then it will be treated again with Adam method. This process will continue switching from stiff to nonstiff vice versa whenever it is necessary until the interval of integration is completed.Next, a block method with R-points generate R new approximate solution values;is a strategy for solving a system and also for parallelizing ODEs. Partitioning this block method to solve stiff differential equations is a new strategy; it is more efficient and takes less computational time compared to the sequential methods. Two partitioning techniques are constructed, Intervalwise Block Partitioning (IBP) and Componentwise Block Partitioning (CBP). Numerical results are compared as validation of its effectiveness. Intervalwise block partitioning will initially treat the systems of equations as nonstiff and solve them using Adams method, by switching to the Backward Differentiation formula when there is a step failure and indication of stiffness. Componentwise block partitioning will place the necessary equations that cause instability and stiffness into the stiff subsystem and solve using Backward Differentiation Formula, while all other equations will still be treated as non-stiff and solved using Adams formula. Parallelizing the partitioning strategies using Message Passing Interface (MPI) is the most appropriate method to solve large system of equations. Parallelizing the right algorithm in the partitioning code will give a better perfonnance with shorter execution times. The graphs of its performance and execution time, visualize the advantages of parallelizing. Differential equations Stiff computation (Differential equations) Parallelizing compilers 2007-04 Thesis http://psasir.upm.edu.my/id/eprint/8531/ http://psasir.upm.edu.my/id/eprint/8531/1/FS_2007_39_IR.pdf text en public doctoral Universiti Putra Malaysia Differential equations Stiff computation (Differential equations) Parallelizing compilers Faculty of Science Ismail, Fudziah English
institution Universiti Putra Malaysia
collection PSAS Institutional Repository
language English
English
advisor Ismail, Fudziah
topic Differential equations
Stiff computation (Differential equations)
Parallelizing compilers
spellingShingle Differential equations
Stiff computation (Differential equations)
Parallelizing compilers
Othman, Khairil Iskandar
Partitioning techniques and their parallelization for stiff system of ordinary differential equations
description A new code based on variable order and variable stepsize component wise partitioning is introduced to solve a system of equations dynamically. In previous partitioning technique researches, once an equation is identified as stiff, it will remain in stiff subsystem until the integration is completed. In this current technique, the system is treated as nonstiff and any equation that caused stiffness will be treated as stiff equation. However, should the characteristics showed the elements of nonstiffness, and then it will be treated again with Adam method. This process will continue switching from stiff to nonstiff vice versa whenever it is necessary until the interval of integration is completed.Next, a block method with R-points generate R new approximate solution values;is a strategy for solving a system and also for parallelizing ODEs. Partitioning this block method to solve stiff differential equations is a new strategy; it is more efficient and takes less computational time compared to the sequential methods. Two partitioning techniques are constructed, Intervalwise Block Partitioning (IBP) and Componentwise Block Partitioning (CBP). Numerical results are compared as validation of its effectiveness. Intervalwise block partitioning will initially treat the systems of equations as nonstiff and solve them using Adams method, by switching to the Backward Differentiation formula when there is a step failure and indication of stiffness. Componentwise block partitioning will place the necessary equations that cause instability and stiffness into the stiff subsystem and solve using Backward Differentiation Formula, while all other equations will still be treated as non-stiff and solved using Adams formula. Parallelizing the partitioning strategies using Message Passing Interface (MPI) is the most appropriate method to solve large system of equations. Parallelizing the right algorithm in the partitioning code will give a better perfonnance with shorter execution times. The graphs of its performance and execution time, visualize the advantages of parallelizing.
format Thesis
qualification_level Doctorate
author Othman, Khairil Iskandar
author_facet Othman, Khairil Iskandar
author_sort Othman, Khairil Iskandar
title Partitioning techniques and their parallelization for stiff system of ordinary differential equations
title_short Partitioning techniques and their parallelization for stiff system of ordinary differential equations
title_full Partitioning techniques and their parallelization for stiff system of ordinary differential equations
title_fullStr Partitioning techniques and their parallelization for stiff system of ordinary differential equations
title_full_unstemmed Partitioning techniques and their parallelization for stiff system of ordinary differential equations
title_sort partitioning techniques and their parallelization for stiff system of ordinary differential equations
granting_institution Universiti Putra Malaysia
granting_department Faculty of Science
publishDate 2007
url http://psasir.upm.edu.my/id/eprint/8531/1/FS_2007_39_IR.pdf
_version_ 1794018763846189056