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Issue title: Digital transformation through advances in artificial intelligence and machine learning
Guest editors: Hasmat Malik, Gopal Chaudhary and Smriti Srivastava
Article type: Research Article
Authors: Raveendran, Arun Prasatha | Alzubi, Jafar A.b; * | Sekaran, Rameshc | Ramachandran, Manikandand
Affiliations: [a] Siddhartha Institute of Technology & Sciences, Hyderabad, Telangana, India | [b] Al-Balqa Applied University, Salt, Jordan | [c] Velagapudi Ramakrishna Siddhartha Engineering College, Vijayawada, Andhra Pradesh, India | [d] SASTRA Deemed University, Thanjavur, India
Correspondence: [*] Corresponding author. Jafar A. Alzubi, Faculty of Engineering, Al-Balqa Applied University, Salt, Jordan. E-mail: [email protected].
Abstract: This Ensuing generation of FPGA circuit tolerates the combination of lot of hard and soft cores as well as devoted accelerators on a chip. The Heterogene Multi-Processor System-on-Chip (Ht-MPSoC) architecture accomplishes the requirement of modern applications. A compound System on Chip (SoC) system designed for single FPGA chip, and that considered for the performance/power consumption ratio. In the existing method, a FPGA based Mixed Integer Programming (MIP) model used to define the Ht-MPSoC configuration by taking into consideration the sharing hardware accelerator between the cores. However, here, the sharing method differs from one processor to another based on FPGA architecture. Hence, high number of hardware resources on a single FPGA chip with low latency and power targeted. For this reason, a fuzzy based MIP and Graph theory based Traffic Estimator (GTE) are proposed system used to define New asymmetric multiprocessor heterogene framework on microprocessor (AHt-MPSoC) architecture. The bandwidths, energy consumption, wait and transmission range are better accomplished in this suggested technique than the standard technique and it is also implemented with a multi-task framework. The new Fuzzy control-based AHt-MPSoC analysis proves significant improvement of 14.7 percent in available bandwidth and 89.8 percent of energy minimized to various traffic scenarios as compared to conventional method.
Keywords: FPGA, MPSoC, hardware accelerators, MIP model, fuzzy control, GTE
DOI: 10.3233/JIFS-189737
Journal: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 2, pp. 647-658, 2022
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