Search
22 articles for “CPU Optimization”
-
A Reviewed Study On Cpu-Optimized Parameter-Efficient Fine- Tuning For Large Language Models To Increase Accuracy Using Lora
Abstract: The fast proliferation of Large Language Models (LLMs) has increased the need to optimize the process of fine-tuning but the existing workflows that require a GPU are still expensive, intensive, and unavailable to most researchers. This paper is driven by the desire to have a more cost-efficient and democratized version by examining a CPU-efficient implementation of Parameter-Efficient Fine-Tuning (PEFT) based on Low-Rank Adaptation (LoRA). The major purpose of the study …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article
-
An Optimised CPU Scheduling Algorithm with Adaptive Time Quantum Approach
Abstract: CPU scheduling is an essential mechanism implemented by the operating system to determine the execution of multiple processes by the CPU. The primary objective of the scheduling algorithms is to optimize the systems’ performance efficiently. The performance of a CPU scheduling algorithm depends on various factors and can be evaluated on various criteria like average turnaround time, average waiting time, throughput, fairness etc. This paper aims to present an optimal …
Published in Journal of Operating Systems Development & Trends Read article
-
Systematic Review of Application of Nature-Inspired Algorithms for Resource Optimization in Multi-Programmed Operating Systems
Abstract: Multi-programmed operating systems are increasingly confronted with complex challenges in efficiently managing system resources, primarily due to the need to handle numerous concurrent processes with diverse and often conflicting resource demands. As these systems evolve, ensuring optimal performance across various dimensions, such as CPU scheduling, memory allocation, and load balancing, has become crucial. In this context, nature-inspired algorithms have emerged as promising solutions for enhancing resource optimization. These algorithms, which …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 08–14 Read article
-
Enhanced Shell Script Optimization Techniques for Low-latency Automation in DevOps Environments
Abstract: Shell scripting remains a foundational component in system administration and DevOps automation, providing a straightforward yet powerful method for automating tasks, managing system configurations, and integrating seamlessly within continuous integration and continuous delivery (CI/CD) pipelines. These scripts serve as the backbone for many repetitive and complex tasks, enabling IT teams to execute workflows efficiently without manual intervention. As organizations continue to scale their infrastructure and adopt more complex architectures, the …
Published in Journal of Advances in Shell Programming · Vol. 11, Issue 3, 2024 · pp. 1–5 Read article
-
Design and Optimization of Domain-Specific Languages for High-Performance Computing Applications
Abstract: The accelerating demand for computational power in scientific, engineering, and data-intensive domains has driven High-Performance Computing (HPC) systems toward unprecedented levels of parallelism and architectural complexity. Contemporary HPC platforms integrate multicore CPUs, many-core GPUs, accelerators, and deep memory hierarchies, creating significant challenges for software development and performance optimization. Traditional general-purpose programming languages and parallel programming frameworks provide low-level control over hardware resources but require extensive manual tuning, resulting in poor …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article
-
Machine Learning Revolutionizing Server Management and Performance
Abstract: The modern data center is a complex and dynamic environment, grappling with ever-increasing workloads, stringent performance demands, and the constant pressure for cost optimization. As such, applying machine learning (ML) directly to the server infrastructure offers a powerful avenue for achieving advanced automation, resource optimization, and proactive problem resolution. This article explores the transformative potential of integrating machine learning into server systems, leveraging insights gleaned from the abstract and conclusion …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 36–44 Read article
-
Dealing with Hardware of the Computers: An Analytical Study
Abstract: The evolution of computer hardware has been pivotal in shaping modern computing capabilities, impacting both personal and professional spheres. This study offers a thorough overview of essential hardware components, such as the central processing unit (CPU), memory, storage devices, motherboards, and input/output peripherals. It explores how advancements in hardware technology, such as the transition from mechanical hard drives to solid-state drives (SSD) and the development of multi-core processors, have enhanced …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 12–21 Read article
-
Review JoEDT N58 Open CPU-Based Milk Collection System
Abstract: The N58 Open CPU-based milk collection system is designed to enhance the efficiency and transparency of milk collection processes in rural and urban dairy operations. By integrating a computerized platform with open-source technology (Open CPU), the system enables real-time monitoring, automatic data logging, and streamlined milk collection from multiple sources. The system allows farmers to register and track their milk deliveries, monitor milk parameters such as fat content and volume, …
Published in Journal of Electronic Design Technology · Vol. 16, Issue 2, 2025 · pp. 17–23 Read article
-
SpecForesight: A Predictive Analytics Pipeline for Laptop Price Forecasting
Abstract: This paper frames laptop pricing as a supervised predictive analytics problem, transforming product specifications into feature-rich signals to forecast price with calibrated regression models and operational guardrails against drift. A structured pipeline ingests tabular listings, performs data cleaning, and engineers domain-informed features (e.g., central processing unit (CPU) family and clocks, graphics processing unit (GPU) tiering, memory/storage density, display, and touch capabilities), followed by encoding and normalization to optimize model learnability. …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 61–71 Read article
-
Real-Time System Monitoring and Resource Optimization Using Shell Scripts in UNIX/Linux Environments
Abstract: Real-time system monitoring is a fundamental aspect of system administration in UNIX/Linux environments, as it ensures optimal system performance, reliability, and continuous availability of services. In modern computing infrastructures, systems are expected to operate efficiently under varying workloads, and any degradation in performance, such as CPU overload, memory exhaustion, disk bottlenecks, or network congestion, can significantly impact user experience and system stability. Regular observation and prompt action are crucial for …
Published in Journal of Advances in Shell Programming · Vol. 13, Issue 1, 2026 · pp. 08–15 Read article
-
Optimizing Image Processing with Verilog on FPGA: Techniques and Performance Enhancements
Abstract: The integration of image processing algorithms into hardware platforms, particularly FPGAs, presents a compelling opportunity for achieving high performance, low latency, and power efficiency in real-time applications. This study focuses on designing and implementing Verilog HDL-based optimal image processing methods for FPGA-based systems. The study explores the development of core algorithms, including edge detection, image enhancement, and adaptive filtering, to maximize resource utilization and processing speed on hardware platforms. Key …
Published in Journal of Semiconductor Devices and Circuits · Vol. 11, Issue 3, 2024 · pp. 46–53 Read article
-
Comparison of Models of Machine Learning and Hyperparameter optimization methods on various datasets
Abstract: The most likely phase in achieving powerful and robust machine learning models is probably the hyperparameters tuning step. The traditional exhaustive methods of search (Grid Search and others) ensure that the search space is covered, but are computationally very inexpensive; random search is less expensive and can still miss good regions; and lastly, the modern model-based and population-based methods (Bayesian Optimization, Tree-structured Parzen Estimator (TPE), Genetic Algorithms) are thought to …
Published in Recent Trends in Programming languages · Vol. 13, Issue 1, 2026 Read article
-
Mood Mate: A Solid-State Edge-AI System for Real-Time Facial Emotion Recognition
Abstract: Recent progress in solid-state electronics and embedded vision systems has enabled real-time emotion-aware applications at the edge. This paper presents MoodMate, a solid-state edge-AI framework for real-time facial emotion recognition using camera-based sensing and embedded processing. The proposed system integrates a solid-state image sensor with an AI- driven emotion classification pipeline optimized for low-latency and resource-constrained environments. Intelligent, emotion-aware apps can now be deployed right at the network edge thanks …
Published in International Journal of Solid State Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 24–30 Read article
-
64 Bit ALU DESIGN USING VEDIC MATHEMATHICS
Abstract: High-speed arithmetic operations are crucial for better performance in contemporary digital systems. Particularly for high bit-width operations, conventional arithmetic logic units (ALUs) frequently experience increased latency and complexity. This work presents the design and implementation of a 64-bit Arithmetic Logic Unit (ALU) using notions from Vedic mathematics. The suggested design makes use of a Kogge-Stone Adder for effective addition and the Urdhva Tiryagbhyam sutra for quick multiplication. Among other mathematical …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
-
Comparison of Various Load Balancing Algorithms in Cloud Computing
Abstract: The components associated with distributed computing are customers, datacenter and appropriated server. One of the principal issuesin distributed computing isload adjusting. Adjusting the heap intends to circulate the outstanding task at hand among a few hubs uniformly so no single hub will be over- burden. Burden can be of any kind that is it very well may be CPU load, memory limit or system load. Right now, introduced a design …
Published in Recent Trends in Parallel Computing Read article
-
Card Fraud Detection Using Artificial Neural Network and Multilayer Perception Algorithm
Abstract: Fraud has posed a significant challenge for merchants, especially in the online business sector, over the course of many years. This is primarily due to the advancements in technology that have made credit card transactions a common method of payment. Credit card fraud refers to the unauthorized use of a credit card by an individual for personal purposes, without the owner's consent and with no intention of paying for the …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 1, Issue 1, 2023 · pp. 21–30 Read article
-
Study and analysis of the Double Data Rate SDRAM Controller for High-speed Interfacing with Processing Device
Abstract: A real-time embedded system must now manage many programs running concurrently. Increased Data Rate Because of its burst access, speed, and pipeline features, synchronous DRAM is a typical memory-building material. DDR transfers are performed using synchronous dynamic access memory. The memory controller must be set with a pipelined design for various applications and systems to perform effectively. The purpose of this study is to design a DRAM controller that will …
Published in Journal of VLSI Design Tools and Technology · Vol. 14, Issue 1, 2024 · pp. 8–13 Read article
-
Optimizing Multi-Cloud Infrastructure: Advanced Bash-Based Automation for Automated Security Patching and Health Monitoring in Hybrid Linux Environments
Abstract: The proliferation of multi-cloud and hybrid Linux environments has introduced significant operational complexity, particularly in maintaining security compliance and system reliability across diverse infrastructure silos. Traditional patch management approaches, relying on manual interventions or disparate vendor-specific tools, suffer from latency, configuration drift, and limited visibility. This article presents a novel, lightweight automation framework constructed entirely in advanced Bash scripting to address automated security patching and real-time health monitoring across hybrid …
Published in Journal of Advances in Shell Programming · Vol. 13, Issue 2, 2026 Read article
-
Designing Digital Filters of Underwater Wireless Sensor Node
Abstract: Underwater Wireless Sensor Networks (UWSNs), an emerging area, integrate sensing, computing, and communication into a single compact device. The digital data is acquired using an FPGA (Field Programmable Gate Array), and the fusion of numerous sensor data is accomplished in the sensor node’s ARM (Advanced RISC Machine) CPU. The sensor interfacing circuit should connect the sensor to the sensor node’s data collecting system. The data from these sensors may be …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 1, Issue 1, 2023 · pp. 43–53 Read article
-
A Review of Blocking Side-Channel Threats in Parallel Cloud Systems
Abstract: Side-channel attacks (SCAs) pose a critical security threat to parallel computing systems, particularly in shared cloud environments where multi-tenancy and resource contention create exploitable vulnerabilities. This study presents a comprehensive review of SCAs in parallel architectures, analyzing attack vectors such as cache-based exploits (e.g., Prime + Probe, Flush + Reload), timing attacks, power analysis, and network-based covert channels. We examine real-world cases including Spectre and Meltdown vulnerabilities that exposed fundamental …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 15–25 Read article