Heuristic Experiments of Threading and Equal Load Partitioning For Hierarchical Heterogeneous Cluster

International Engineering Research and Innovation Symposium

Khalid, Noor Elaiza Abdul^1 ; Hashim, Rathiah^2 ; Noor, Noorhayati Mohamed^1 ; Rosli, Muhammad Helmi^1 ; Manaf, Mazani^1

Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Shah Alam, Selangor, Malaysia^1

Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Parit Raja, Malaysia^2

关键词: Computing resource;    Heterogeneous clusters;    Homogeneous cluster;    Multi core;    Parallel processing;    Performance evaluations;    Sobel edge detection;    Task partitioning;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/160/1/012099/pdf
DOI  :  10.1088/1757-899X/160/1/012099

来源: IOP

【 摘 要 】

Presently, the issue of processing large data on a timely manner poses as a challenge to many ICT researchers. Most commodity computers are interconnected in a network forming a cluster computing resource simulating a super computer. This paper explores heuristically the performance of homogeneous, heterogeneous and multi-core clusters. This work consists of five experiments: Equal task partitioning according to the number of nodes in homogeneous cluster, number of nodes in heterogeneous cluster, number of nodes in heterogeneous cluster with multithreading, number of cores in heterogeneous cluster and number of cores in heterogeneous cluster with multithreading. The task is Sobel edge detection method tested with an array of images. The images are processed in three different sizes; 1K × 1K, 2K × 2K and 3K × 3K. The performance evaluations are based on processing speed. The results yield promising impact of equal partitioning and threading in parallel processing hierarchical heterogeneous cluster.