Search
78 articles for “Low-Power Computing”
-
Spintronic Logic Device Modeling and Energy Optimization for Beyond-CMOS Computing Systems
Abstract: The continuous scaling limitations of conventional CMOS technology have accelerated the exploration of alternative computing paradigms for next-generation low-power and high-performance systems. Spintronic logic devices have emerged as a promising solution due to their non-volatility, ultra-low switching energy, high integration density, and compatibility with beyond-CMOS architectures. This research presents a comprehensive modeling and energy optimization framework for spintronic logic devices applied in beyond- CMOS computing systems. The proposed work investigates …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
-
Neuromorphic Spiking Neural Networks and Event-Driven Hardware: Architectures, Learning Paradigms, and Experimental Realizations
Abstract: With the current computational boom the research community is seeking for more sustainable energy efficient i.e. biologically inspired models of conventional Artificial Neural Networks (ANNs). Spiking Neural Networks (SNNs) known as the third generation of neural network models, provide a revolutionary approach by mimicking the asynchronized event-driven and temporally accurate signaling of the mammalian brain. Whereas conventional deep learning models operate with real-valued activations and dense matrix multiplications, SNNs use …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 Read article
-
Power and Area - Aware Recursive Multiplier Architecture Utilizing Polymer Composites for Neural Network Acceleration
Abstract: Approximate computing is widely applied in error - tolerant systems as an effective technique to enhance circuit performance by deliberately allowing occasional inaccuracies instead of strictly ensuring precise results for every computation. Among the fundamental building blocks of digital systems, multipliers play a crucial role in signal processing, control systems, and machine learning applications; however, they demand significant power, silicon area, and timing resources. Leveraging error - tolerant approximate multipliers …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1320–1337 Read article
-
Novel approaches to the Design and Optimization of Universal Shift Register with Reversible logic
Abstract: Reversible logic is gaining importance in new multi-disciplinary fields, such as quantum computing, low-power computing, and even nanotechnology. The study of reversible gates has quickly evolved as a distinctive area of research as a result of the new developments aimed at fully utilizing resources and performing operations without any loss of information. With chip integration, these USRs, or Universal Shift Registers, have now become fundamental sequential components needed in various …
Published in Journal of VLSI Design Tools and Technology · Vol. 15, Issue 3, 2025 · pp. 21–28 Read article
-
Sustainable Computing: Pioneering Energy-Efficient Innovations for a Greener Digital Future
Abstract: Sustainable computing is an emerging field that focuses on developing environmentally responsible and energy-efficient computing technologies. As the global demand for computing power continues to rise, so does the environmental impact of data centers, hardware manufacturing, and energy consumption.This article explores the key principles of sustainable computing, including energy-efficient hardware design, green data centers, and the role of software optimization in reducing energy consumption. We discuss the importance of adopting …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 15, Issue 2, 2025 · pp. 32–45 Read article
-
A Neuromorphic-Inspired, Low-Power VLSI Architecture for Edge AI in IoT Sensor Nodes
Abstract: As the proliferation of Internet of Things (IoT) devices continues to rise, there is an increasing demand for real-time, energy-efficient artificial intelligence (AI) processing directly at the network edge. Traditional edge AI accelerators, often based on deep learning models like convolutional neural networks (CNNs), struggle to meet the ultra-low-power requirements of battery-constrained IoT sensor nodes. In response to this challenge, this study introduces a neuromorphic-inspired, low-power very- large-scale integration (VLSI) …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 2, 2025 · pp. 41–47 Read article
-
Simulation of Adder Circuit Using Reversible Gates in Verilog HDL
Abstract: The emerging field of quantum computing uses quantum logic gates. The reversibility of logic gates is an important aspect of quantum logic gates used in VLSI and quantum computing. Reversibility ensures that power consumption is minimized. This study explores the field of reversible logic and utilizes Peres gate to develop a full adder circuit that shows a significant reduction in power consumption in simulations performed in Xilinx Vivado. We have …
Published in Journal of VLSI Design Tools and Technology · Vol. 14, Issue 3, 2024 · pp. 32–38 Read article
-
Advances in Data Security in Cryptography
Abstract: In the ultra-modern period, evaluation of networking and wireless networks within information and communication technology has brought many changes to deal with this technology using internet, growing strongly over the past several decades, data security has come a main concern for anyone connected to the web. Data security ensures that our data can only be accessed by authorized recipients and prevents any unauthorized access or alteration of the data. We …
Published in Journal Of Network security · Vol. 12, Issue 1, 2024 · pp. 1–7 Read article
-
Ferroelectric Materials for Next-Generation Non-Volatile Memory Applications
Abstract: The continuous scaling of conventional memory technologies is increasingly constrained by limitations in power consumption, speed, endurance, and integration density. As data-intensive applications such as artificial intelligence, Internet of Things, and edge computing demand fast and energy-efficient memory solutions, alternative non-volatile memory technologies have gained significant attention. Ferroelectric materials, characterized by their reversible spontaneous polarization, offer a promising pathway toward next-generation non-volatile memory due to their intrinsic non-volatility, low operating …
Published in Journal of Microelectronics and Solid State Devices · Vol. 13, Issue 1, 2026 · pp. 1–9 Read article
-
MAC Unit Implementation on FPGA
Abstract: Multiply–accumulate (MAC) computations account for a large part of machine learning accelerator operations. The pipelined structure is usually adopted to improve the performance by reducing the length of critical paths. An increase in the number of flip-flops due to pipelining, however, generally results in significant area and power increase. Using this method, we create and build a cutset-free feedforward MAC architecture that maximizes data propagation and removes superfluous pipeline registers. …
Published in Journal of Microcontroller Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 29–37 Read article
-
IoT-Enabled Sustainable Development: Architectures, Applications, Challenges, and Future Directions
Abstract: The Internet of Things (IoT) has developed into a powerful technology that can help tackle key global sustainability issues by enabling real-time monitoring, supporting data-based decisions, and facilitating smart automation. By interconnecting physical devices, sensors, and communication networks, IoT enables continuous data collection and analysis that supports efficient resource utilization across multiple sectors such as energy, agriculture, water management, transportation, and urban infrastructure. Through smart sensing and automated control systems, …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 2, 2026 Read article
-
AI Driven IoT Based Decision Making System for Brain wave study: KSK approach for Brain wave study
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain-computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
-
A Comprehensive Review on IoT and Edge Computing in Electronics: Trends, Challenges, and Future Directions
Abstract: The Internet of Things (IoT) transformed the electronics industry by enabling ubiquitous connectivity between billions of devices. This has created an unprecedented amount of data, challenging traditional cloud-based architectures with latency, bandwidth, and security issues. Edge computing came as an additive architecture by distributing computation and bringing intelligence to IoT edges to provide real-time responsiveness and reduce dependence on centralized infrastructure. This study offers a thorough analysis of current developments …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 1, 2026 · pp. 1–9 Read article
-
QCA-based Implementation of Budget-friendly and Energy-Efficient Exclusive-OR/Exclusive-NOR Gates
Abstract: Quantum-dot cellular automata (QCA) is a novel nanoscale computational approach that proposes reduced dimensions, lower power consumption, increased speed, and deliberate design as a solution to the scaling challenge associated with CMOS technique. QCA is a nascent nanotechnology that utilizes the Coulomb repulsion principle. Quantum computing has emerged as a highly effective paradigm for the creation of energy-efficient hardware at the nanoscale. This article presents implementation of a very efficient …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 1, Issue 2, 2023 · pp. 1–6 Read article
-
Next-generation Operating Systems: AI-driven Autonomy, Quantum Integration, and Edge Computing
Abstract: The rapid evolution of computing paradigms is driving the need for next-generation operating systems that seamlessly integrate artificial intelligence, quantum computing, and edge processing. Traditional operating systems, while efficient for classical computation, lack the necessary capabilities to handle real-time AI-driven decision-making, quantum processing, and decentralized edge networks. This study explores how future operating systems will incorporate AI-driven autonomy to enhance resource management, quantum integration to leverage superior computational power, and …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 1, 2025 · pp. 25–36 Read article
-
Photonic-Assisted Spintronic Solid-State Switching Model for High-Speed Memory Devices
Abstract: The rapid advancement of high-speed computing and data-centric applications has intensified the demand for energy-efficient and ultra-fast memory technologies. This paper proposes a Photonic-Assisted Spintronic Solid-State Switching Model for next-generation high-speed memory devices. The proposed framework integrates photonic excitation mechanisms with spintronic switching dynamics to enhance data transfer speed, minimize switching delay, and reduce power dissipation in solid-state memory architectures. By combining optical pulse-assisted spin polarization with magnetic tunnel junction-based …
Published in International Journal of Solid State Innovations & Research · Vol. 4, Issue 1, 2026 Read article
-
An Efficient Counter Using Modified Upper and Lower SVL Techniques and TSPCL
Abstract: Low power VLSI has emerged as the fundamental building block of the modern electronic era. This leads to a substantial paradigm shift where both power dissipation, performance and area of utmost importance. In the earlier time of fabrication, power dissipation was mainly neglected due to low device density and low operating frequency needed for computation. But in modern technological era, the need for high device density, higher operating frequency, proliferation …
Published in Research & Reviews : Journal of Physics · Vol. 13, Issue 2, 2024 · pp. 37–43 Read article
-
Machine Learning–Guided Cognitive RF System with Dynamic FFT Resolution and Multiplier Reconfiguration for Adaptive Anti-Jamming Communication
Abstract: This paper presents a hierarchical adaptive RF communication system that integrates signal quality-based pre- processing with machine learning-driven signal classification to achieve robust and resource-efficient operation in dynamic, interference-prone environments. Unlike prior art that addresses adaptive RF, ML classification, or anti-jamming individually, this work uniquely combines real-time SNR/RSSI-based signal strength estimation with dynamic FFT size selection (64-, 256- , or 512-point) and arithmetic-level multiplier reconfiguration (CORDIC, Distributed Arithmetic, and hybrid …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article
-
Low-Power Reconfigurable Digital Filter Design Using FPGA for IoT Edge Devices
Abstract: The rapid evolution of the Internet of Things (IoT) has led to an exponential increase in the deployment of edge devices that continuously process real-time sensor data under strict power, latency, and computational constraints. Digital filtering remains a critical operation in these devices, supporting tasks such as noise removal, data conditioning, and feature extraction for intelligent decision-making. However, conventional filter implementations on microcontrollers or fixed digital signal processors often struggle …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 3, Issue 2, 2025 · pp. 23–34 Read article
-
Design and Performance Analysis of Silicon Photonic Waveguides for High-Speed Optical Communication
Abstract: The exponential growth of data traffic in data centers and high-performance computing systems necessitates a paradigm shift from conventional electrical interconnects to high- speed, low-power on-chip optical interconnects. Silicon Photonics (SiP) is the leading platform for this transition due to its compatibility with CMOS manufacturing and the high- index contrast between silicon (Si) and silicon dioxide (SiO 2 ). This paper details the design, simulation, and comprehensive performance analysis of …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 29–37 Read article