Scheduling of dynamically evolving parallel programs using the genetic approach
Scheduling of dynamically evolving parallel programs in distributed multiprocessor systems, with different interconnection topologies, is the focus of this study. Each parallel program dynamically evolves during execution time and resulted in a tree-like execution structure. Due to this behavior of...
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| Other Authors: | |
| Format: | Thesis |
| Language: | English |
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2011
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| Online Access: | http://hdl.handle.net/10356/42693 |
| _version_ | 1824454722868740096 |
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| author | Ooi, Boon Pin. |
| author2 | School of Applied Science |
| author_facet | School of Applied Science Ooi, Boon Pin. |
| author_sort | Ooi, Boon Pin. |
| collection | NTU |
| description | Scheduling of dynamically evolving parallel programs in distributed multiprocessor systems, with different interconnection topologies, is the focus of this study. Each parallel program dynamically evolves during execution time and resulted in a tree-like execution structure. Due to this behavior of the parallel programs, dynamic task scheduling is the technique that is applied here. The parallel programs are scheduled to be run on several interconnection topologies. They are uniprocessor Ethernet, multiprocessors Ethernet, ring, mesh, and hypercube. These topologies are chosen due to their popularity in today's multiprocessor systems. Other researchers have proposed many dynamic schedulers. Among these approaches, many employed search techniques such as genetic algorithm, simulated annealing, hillclimbing,
and branch-and-bound. Genetic algorithms have been shown to be a promising
technique due to its capability in exploring the solution space. Therefore, the four proposed dynamic schedulers here are based on genetic algorithm. These schedulers are considered as centralized approaches due to the exclusive reservation of one processor for their execution. |
| first_indexed | 2025-02-19T03:26:50Z |
| format | Thesis |
| id | ntu-10356/42693 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2025-02-19T03:26:50Z |
| publishDate | 2011 |
| record_format | dspace |
| spelling | ntu-10356/426932020-09-27T20:18:43Z Scheduling of dynamically evolving parallel programs using the genetic approach Ooi, Boon Pin. School of Applied Science Huang Shell Ying DRNTU::Engineering::Computer science and engineering::Computer systems organization::Computer-communication networks Scheduling of dynamically evolving parallel programs in distributed multiprocessor systems, with different interconnection topologies, is the focus of this study. Each parallel program dynamically evolves during execution time and resulted in a tree-like execution structure. Due to this behavior of the parallel programs, dynamic task scheduling is the technique that is applied here. The parallel programs are scheduled to be run on several interconnection topologies. They are uniprocessor Ethernet, multiprocessors Ethernet, ring, mesh, and hypercube. These topologies are chosen due to their popularity in today's multiprocessor systems. Other researchers have proposed many dynamic schedulers. Among these approaches, many employed search techniques such as genetic algorithm, simulated annealing, hillclimbing, and branch-and-bound. Genetic algorithms have been shown to be a promising technique due to its capability in exploring the solution space. Therefore, the four proposed dynamic schedulers here are based on genetic algorithm. These schedulers are considered as centralized approaches due to the exclusive reservation of one processor for their execution. Master of Applied Science 2011-01-07T02:42:25Z 2011-01-07T02:42:25Z 1998 1998 Thesis http://hdl.handle.net/10356/42693 en 216 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Computer science and engineering::Computer systems organization::Computer-communication networks Ooi, Boon Pin. Scheduling of dynamically evolving parallel programs using the genetic approach |
| title | Scheduling of dynamically evolving parallel programs using the genetic approach |
| title_full | Scheduling of dynamically evolving parallel programs using the genetic approach |
| title_fullStr | Scheduling of dynamically evolving parallel programs using the genetic approach |
| title_full_unstemmed | Scheduling of dynamically evolving parallel programs using the genetic approach |
| title_short | Scheduling of dynamically evolving parallel programs using the genetic approach |
| title_sort | scheduling of dynamically evolving parallel programs using the genetic approach |
| topic | DRNTU::Engineering::Computer science and engineering::Computer systems organization::Computer-communication networks |
| url | http://hdl.handle.net/10356/42693 |
| work_keys_str_mv | AT ooiboonpin schedulingofdynamicallyevolvingparallelprogramsusingthegeneticapproach |