Work place: Dept. of Computer Science and Engineering, IMS Engineering College, Ghaziabad, Uttar Pradesh, India
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Research Interests: Computer systems and computational processes, Computational Learning Theory, Data Structures and Algorithms
Biography
Ms. Shaili Gupta has completed her M.Tech from Banasthali university, Rajasthan in 2010. Currently she is working in IMS Engineering College, Ghaziabad. Her area of interest is machine learning and deep learning.
By Surendra Kumar Shukla Devesh Pratap Singh Shaili Gupta Kireet Joshi Vishan Kumar Gupta
DOI: https://doi.org/10.5815/ijwmt.2022.04.02, Pub. Date: 8 Aug. 2022
Multi-core systems are outperforming nowadays. Therefore, various computing paradigms are intrinsically incorporated in the multicore domain to exploit its potential and solve well known computing problems. Parameter tuning is a well-known computing problem in the field of Multicore domain. Addressing the said hurdle would leverage in the performance enhancement of Multicore systems. Various efforts in this direction have been made through the conventional parameter tuning algorithms in a limited scope; however, the problem is yet not addressed completely. In this research article, we have addressed parameter tuning problem by employing applications of graph theory, especially Dijkstra shortest path algorithm to address the said issue. Dijkstra’s principle has been applied to establish correlation among the parameters further tuning by finding the pair of suitable parameters. Two other algorithms which are based on application feedback (to provide performance goals to the system) has been introduced. The proposed algorithms collectively (as a framework), addressed the parameter tuning problem. The effectiveness of the algorithms is verified and further measured in distinct parameter tuning scenarios and promising outcome has been achieved.
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