Journal of VLSI Circuits and Systems

Impact of Digital Technologies on Economic and Marketing Innovation and Competitiveness within VLSI System Employment

Solomiya Ohinok — 2025-01-20

This article examines the role of digital technologies in shaping economic and marketing innovation and competitiveness for firms engaged in employment in Very Large Scale Integration (VLSI) systems. The evolution of semiconductor technology has made
integrating digital technologies a critical part of innovation in VLSI design, production, and application. The study begins by exploring the current state of play in VLSI technology and the role of digitalization in enhancing operational efficiencies and fostering innovative
approaches to product development. An extensive analysis of recent developments in VLSI systems employment demonstrates how digital technologies such as artificial intelligence (AI), machine learning, and automation can facilitate improved design optimization, yield enhancement, and reduce time-to-market for semiconductor products. The enhanced design efficiencies and timely product development accruing from applying digital technologies translate into a greater competitive advantage for firms in a global marketplace. The article examines the synergies between digital technologies and economic innovation. It highlights how firms can leverage digital technologies to enhance data analytics and advanced manufacturing processes, creating more intelligent and capable VLSI systems for next-generation electronics, telecommunications, consumer goods, and many other applications. The article concludes by contending that embracing digital technologies is necessary and critical for economic innovation and competitiveness for firms engaged in VLSI systems employment. The article also calls for further examination of emerging digital tools and platforms to shape the semiconductor industry’s trajectory at a much faster pace, leading to more robust economic growth and technological advancement.

Design and Optimization of Coarse-Grained Reconfigurable Array (CGRA) Architecture for Efficient Processing-in-Memory (PIM) Systems

Anas A. Salameh — 2025-01-20

The Coarse-Grained Reconfigurable Array (CGRA) architecture for Efficient Processing-in-Memory (PIM) systems is presented in this article. PIM architectures that incorporate computational capabilities directly into memory present a promising solution to mitigate the memory wall issue. There are several difficulties in CGRA architecture optimization for PIM systems especially when it comes to striking a balance between area efficiency, power consumption and performance. The proposed framework tackles these problems by examining crucial design components like processing element (PE) architecture memory hierarchy integration and interconnect design. Using a design space exploration (DSE) methodology we assess various CGRA configurations to find the optimal trade-offs between computation throughput, power consumption and silicon area utilization. To assist in selecting effective architectures that meet different application workloads the framework combines performance analysis and advanced modeling techniques. Based on test results, the optimized CGRA architecture for PIM achieves significant improvements in processing performance (20 percent increase in throughput), area reduction and energy efficiency (up to 40 percent reduction in power consumption) when compared to conventional PIM designs. Our architecture is well-suited for data-intensive applications such as machine learning and graph analytics since these enhancements are achieved without compromising computational accuracy or scalability.

Adaptive VLSI Design Using Dynamic Voltage and Frequency Scaling (DVFS) for Low-Latency IoT Communication Networks

Anas A. Salameh — 2025-01-20

The best and most compatible hardware solutions need to be developed to meet the growing demand for communication in Internet of Things (IoT) networks. This paper suggests using dynamic voltage and frequency scaling or DVFS for designing adaptive VLSI circuits for small IoT communication networks. DVFS is used to adjust the operating voltage and frequency of circuits and reduce power consumption when network traffic is light. It also maintains high-speed operation under heavy loads. By satisfying the requirements of the oscillating network the proposed VLSI design preserves low latency and high power efficiency. Simulations and prototype implementations show that in comparison to conventional VLSI designs the system features notable improvements in both communication speed and power consumption. These findings show that by strengthening power and traffic performance in IoT networks through the integration of VLSI circuits DVFS can be a good option for resource-constrained IoT devices and real-time applications.

Design of a optimized CMOS Differential Amplifier using Craziness-based PSO

Sandeep Kumar Dash — 2025-01-29

Particle swarm optimization (PSO) is acomputational method used for solving different types of optimization problems. The social behaviors of fish schooling and flocks of birds mostly influence the PSO. PSO uses a collection of particles to explore the search space and locate the best possible solution.Each particle updates its position depending upon experience of itself or from neighboring particles, aiming to find the best solution in terms of the objective function being optimized.Crazinessbased Particle Swarm Optimization (CRPSO) is an advanced variation of the standard Particle Swarm Optimization (PSO) algorithm.CRPSO introduces a "craziness" factor to enhance the diversity of the swarm and prevent premature convergence to local optima.This paper deals with the design of a CMOS differential amplifier circuit with a current mirror load using CRPSO algorithm. The optimized sizes of the transistors are obtained using CRPSO to decrease the overall transistor area while meeting design limitations. The results achieved using the CRPSOare validated in the SPICE. The simulation result shows the superiority of CRPSO in the design of differential amplifier.