Dynamic partitioning and data allocation method on heterogeneous architecture / Muhammad Helmi Rosli

In recent years, processing large data set to produce result in a timely manner poses a lot of challenges to ICT researchers. Currently most organization has an elaborate local network system whose computers are underutilized. These network form cluster of computing resources that simulates supercom...

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Main Author:	Rosli, Muhammad Helmi
Format:	Thesis
Language:	English
Published:	2015
Subjects:	Supercomputers. High performance computing
Online Access:	http://ir.uitm.edu.my/id/eprint/15723/ http://ir.uitm.edu.my/id/eprint/15723/1/TM_MUHAMMAD%20HELMI%20ROSLI%20CS%2015_5.PDF

id	uitm-15723
recordtype	eprints
spelling	uitm-157232016-12-20T02:23:10Z http://ir.uitm.edu.my/id/eprint/15723/ Dynamic partitioning and data allocation method on heterogeneous architecture / Muhammad Helmi Rosli Rosli, Muhammad Helmi Supercomputers. High performance computing In recent years, processing large data set to produce result in a timely manner poses a lot of challenges to ICT researchers. Currently most organization has an elaborate local network system whose computers are underutilized. These network form cluster of computing resources that simulates supercomputer. Processing images are computationally complex due to its data and task intensive nature. This can be solved by parallelizing the process in cluster environment. Most cluster environment have a variety of computer hardware specification namely heterogeneous environment.Optimizing the resources in heterogeneous environment during parallel processing is not a simple task. These involves partitioning and allocating task to each cluster node.The aim of these research is to investigate various method of partitioning and allocating task in cluster environment and produce a dynamic partitioning and allocating method. Initial stage of the research consist of exploring the heuristic performance of cluster and multi-threading involving five experiments; homogeneous architecture with node partitioning; heterogeneous architecture with node partitioning; heterogeneous architecture with node partitioning including multi-threading; heterogeneous architecture with node and core partitioning; heterogeneous architecture with node and core partitioning including multi-threading.The performances use sequential processing speed as a benchmark. Each experiment highlight the advantages and disadvantages of the experimental architecture.The disadvantages from each experiment prompts the design of dynamic parallel partitioning and allocating framework. The case study use for this experiment is Sobel edge detection algorithm. The test data set focuses on processing images of three different sizes; (IK x IK), (2K x 2K) and (3K x 3K). The performance evaluation is based on the processing speed in second, speedup, and efficiency. In conclusion, it is found that in idle situation heterogeneous architecture with node and core partitioning including multi-threading perform better from other experiment. However, in real working condition where some computer are serving users processes, the dynamic algorithm provides a potential alternative. 2015 Thesis NonPeerReviewed text en http://ir.uitm.edu.my/id/eprint/15723/1/TM_MUHAMMAD%20HELMI%20ROSLI%20CS%2015_5.PDF Rosli, Muhammad Helmi (2015) Dynamic partitioning and data allocation method on heterogeneous architecture / Muhammad Helmi Rosli. Masters thesis, Universiti Teknologi MARA.
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Teknologi MARA
building	UiTM Institutional Repository
collection	Online Access
language	English
topic	Supercomputers. High performance computing
spellingShingle	Supercomputers. High performance computing Rosli, Muhammad Helmi Dynamic partitioning and data allocation method on heterogeneous architecture / Muhammad Helmi Rosli
description	In recent years, processing large data set to produce result in a timely manner poses a lot of challenges to ICT researchers. Currently most organization has an elaborate local network system whose computers are underutilized. These network form cluster of computing resources that simulates supercomputer. Processing images are computationally complex due to its data and task intensive nature. This can be solved by parallelizing the process in cluster environment. Most cluster environment have a variety of computer hardware specification namely heterogeneous environment.Optimizing the resources in heterogeneous environment during parallel processing is not a simple task. These involves partitioning and allocating task to each cluster node.The aim of these research is to investigate various method of partitioning and allocating task in cluster environment and produce a dynamic partitioning and allocating method. Initial stage of the research consist of exploring the heuristic performance of cluster and multi-threading involving five experiments; homogeneous architecture with node partitioning; heterogeneous architecture with node partitioning; heterogeneous architecture with node partitioning including multi-threading; heterogeneous architecture with node and core partitioning; heterogeneous architecture with node and core partitioning including multi-threading.The performances use sequential processing speed as a benchmark. Each experiment highlight the advantages and disadvantages of the experimental architecture.The disadvantages from each experiment prompts the design of dynamic parallel partitioning and allocating framework. The case study use for this experiment is Sobel edge detection algorithm. The test data set focuses on processing images of three different sizes; (IK x IK), (2K x 2K) and (3K x 3K). The performance evaluation is based on the processing speed in second, speedup, and efficiency. In conclusion, it is found that in idle situation heterogeneous architecture with node and core partitioning including multi-threading perform better from other experiment. However, in real working condition where some computer are serving users processes, the dynamic algorithm provides a potential alternative.
format	Thesis
author	Rosli, Muhammad Helmi
author_facet	Rosli, Muhammad Helmi
author_sort	Rosli, Muhammad Helmi
title	Dynamic partitioning and data allocation method on heterogeneous architecture / Muhammad Helmi Rosli
title_short	Dynamic partitioning and data allocation method on heterogeneous architecture / Muhammad Helmi Rosli
title_full	Dynamic partitioning and data allocation method on heterogeneous architecture / Muhammad Helmi Rosli
title_fullStr	Dynamic partitioning and data allocation method on heterogeneous architecture / Muhammad Helmi Rosli
title_full_unstemmed	Dynamic partitioning and data allocation method on heterogeneous architecture / Muhammad Helmi Rosli
title_sort	dynamic partitioning and data allocation method on heterogeneous architecture / muhammad helmi rosli
publishDate	2015
url	http://ir.uitm.edu.my/id/eprint/15723/ http://ir.uitm.edu.my/id/eprint/15723/1/TM_MUHAMMAD%20HELMI%20ROSLI%20CS%2015_5.PDF
first_indexed	2023-09-18T22:54:30Z
last_indexed	2023-09-18T22:54:30Z
_version_	1777417763322593280

Dynamic partitioning and data allocation method on heterogeneous architecture / Muhammad Helmi Rosli

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