A CRCLA Task Partition Algorithm Combining Genetic Algorithm and Clustering Based Partitioning Algorithm

2020 ◽  
Author(s):  
Yulei Zhang ◽  
Jinfu Xu ◽  
Wei Li ◽  
Longmei Nan ◽  
Tao Chen
Keyword(s):  
Genetic Algorithm ◽  
Partitioning Algorithm ◽  
Task Partition

scholarly journals A genetic algorithm based partition generation and optimization method for finite element problems

2021 ◽  
Author(s):  
Lubomir Jirasek
Keyword(s):  
Genetic Algorithm ◽  
Load Balance ◽  
Optimization Problem ◽  
Direct Method ◽  
Optimization Method ◽  
Time Savings ◽  
Partitioning Algorithm ◽  
A Direct Method ◽  
Single Processor ◽  
Compute Time

A two-step partitioning algorithm for FE meshes is proposed in this work for the purposes of time savings. A direct method based on the concept of 'separateness' was applied first, followed by a partition optimization process that used a Genetic Algorithm (GA). A total of 9 applications were evaluated to demonstrate the durability, versatility, and effectiveness of this partitioning algorithm with respect to interface node count and subdomain load balance. Beyond this wingbox optimization problem was performed on a single processor using a GA to demonstrate the possible time savings of the method. With a 30% decrease in compute time witnessed, it can be said with confidence that the propose partitioning algorithm was a success.

Hardware/Software Partitioning Algorithm Based on Genetic Algorithm

2014 ◽  
Vol 9 (6) ◽  
Author(s):  
Shuai Guo Li ◽  
Fu Jin Feng ◽  
Hua Jun Hu ◽  
Cong Wang ◽  
Duo Qi
Keyword(s):  
Genetic Algorithm ◽  
Partitioning Algorithm ◽  
Software Partitioning

scholarly journals A genetic algorithm based partition generation and optimization method for finite element problems

2021 ◽  
Author(s):  
Lubomir Jirasek
Keyword(s):  
Genetic Algorithm ◽  
Load Balance ◽  
Optimization Problem ◽  
Direct Method ◽  
Optimization Method ◽  
Time Savings ◽  
Partitioning Algorithm ◽  
A Direct Method ◽  
Single Processor ◽  
Compute Time

A two-step partitioning algorithm for FE meshes is proposed in this work for the purposes of time savings. A direct method based on the concept of 'separateness' was applied first, followed by a partition optimization process that used a Genetic Algorithm (GA). A total of 9 applications were evaluated to demonstrate the durability, versatility, and effectiveness of this partitioning algorithm with respect to interface node count and subdomain load balance. Beyond this wingbox optimization problem was performed on a single processor using a GA to demonstrate the possible time savings of the method. With a 30% decrease in compute time witnessed, it can be said with confidence that the propose partitioning algorithm was a success.

The ground state energy of the ±J spin glass from the genetic algorithm

1994 ◽  
Vol 4 (9) ◽  
pp. 1281-1285 ◽  
Author(s):  
P. Sutton ◽  
D. L. Hunter ◽  
N. Jan
Keyword(s):  
Genetic Algorithm ◽  
Spin Glass ◽  
Ground State Energy ◽  
Ground State ◽  
State Energy
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