A novel approach for CPU utilization on a multicore paradigm using parallel quicksort

Multicore architecture of CPU is popular because of its performance; the challenge for the Multicore environment are-writing the effective code that can exploit the parallelism, measuring the performance in terms of CPU individual core utilization. The effective code using multithreading (parallel c...

Full description

Saved in:

Bibliographic Details
Published in:	2017 3rd International Conference on Computational Intelligence & Communication Technology (CICT) pp. 1 - 6
Main Authors:	Singh, Tinku, Srivastava, Durgesh Kumar, Aggarwal, Alok
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01-02-2017
Subjects:	C# languages Central Processing Unit Computational intelligence Conferences Integrated circuits Multicore Multicore processing Parallel Parallel processing processor sorting speedup
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Description
Summary:	Multicore architecture of CPU is popular because of its performance; the challenge for the Multicore environment are-writing the effective code that can exploit the parallelism, measuring the performance in terms of CPU individual core utilization. The effective code using multithreading (parallel code) leads to performance speedup. Various multithreading applications are getting developed now days to utilize the CPU cores. In this paper, tools are developed, one by using C# console viz. application for measuring the performance of the CPU cores individually. Performance is measured in terms of load on each core in percentage. Second tool is designed using windows C# viz. application for plotting the graph with respect to time of CPU load in percentage. By both the tools performance is measured while quicksort is getting executed in the serial and parallel for a large number of data elements. Experiment is done on dual core and quad core CPU and results are stored in the table. Comparison graphs are drawn for running time of quicksort as well as CPU individual core utilization. The result shows parallel version of quicksort better utilize the CPU individual cores compared to its sequential version. It exploits more parallelism that leads the better CPU utilization.
DOI:	10.1109/CIACT.2017.7977382