Efficient Parallelization and Performance Analysis of Meta-heuristics on Many-core Platforms

Simple item page
dc.contributor.authorKumar, Manoj
dc.date.accessioned2024-07-03T07:00:28Z
dc.date.available2024-07-03T07:00:28Z
dc.date.issued2023
dc.descriptionSupervisor: Mitra, Pinakien_US
dc.description.abstractMeta-heuristics are an efficient method for solving complex problems in science, engineering, and industry. They explore the solution space efficiently to generate a good solution in a reasonable time through a neighborhood or population-based local search. Even if the meta-heuristics do it efficiently, for large instances (practical problems of science, engineering, or industry), generation of neighborhood and evaluation of solution of single-solution based meta-heuristics or population-based meta-heuristics takes a tremendous amount of time.en_US
dc.identifier.otherROLL NO.146101013
dc.identifier.urihttps://gyan.iitg.ac.in/handle/123456789/2665
dc.language.isoenen_US
dc.relation.ispartofseriesTH-3109
dc.subjectMeta-heuristicsen_US
dc.subjectMulti-Core Architectureen_US
dc.subjectGPUen_US
dc.subjectCUDAen_US
dc.titleEfficient Parallelization and Performance Analysis of Meta-heuristics on Many-core Platformsen_US
dc.typeThesisen_US
Files
Original bundle
Now showing 1 - 2 of 2
No Thumbnail Available
Name:
Abstract-TH-3109_146101013.pdf
Size:
78.51 KB
Format:
Adobe Portable Document Format
Description:
ABSTRACT
Download
No Thumbnail Available
Name:
TH-3109_146101013.pdf
Size:
2.44 MB
Format:
Adobe Portable Document Format
Description:
THESIS
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed to upon submission
Description:
Download
Collections
PhD Theses (Computer Science and Engineering)