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473 articles for “computing performance”
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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
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Algorithmic Strategies for Complex Data Handling: Optimizing Data Structures for Enhanced Computational Performance
Abstract: We live in an age of big data and processing very large often complicated datasets can be crucial to efficient algorithmic performance. This paper discusses different algorithmic techniques when working with difficult data and how to arrange your information structures correctly for better functionality in large-scale methods. It checks the impact of different algorithms like sorting, searching, and hashing in boosting its processing speed as well as memory use. This …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 2, 2024 · pp. 1–10 Read article
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Next-Gen Techniques for Bottleneck Detection in High-Performance Computing
Abstract: Modern computing systems face new challenges in bottleneck detection and mitigation due to their increasing complexity which stems from multi-core architectures alongside distributed platforms and real-time processing needs. Traditional methods like hardware profiling and static analysis which used to work well now struggle to keep up with the changing conditions of dynamic system behaviors and diverse computing environments along with variable workload patterns. The current limitations restrict their capability to …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 09–14 Read article
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The Impact of High-Performance Computing on FEA and CFD Simulations
Abstract: The integration of advanced simulation techniques, such as Finite Element Analysis (FEA) and Computational Fluid Dynamics (CFD), has transformed mechanical design by enabling engineers to develop optimized, efficient, and reliable systems. FEA is widely applied to analyze structural mechanics, thermal stresses, and vibrations, offering detailed insights into material behavior and design performance. On the other hand, CFD focuses on simulating fluid flow, heat transfer, and aerodynamic performance, making it indispensable …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 26–35 Read article
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Enhancing Data Processing and Storage in Computing Environments: A Survey on the Use of NVMe SSDs
Abstract: In the current era of fast pace technological growth, the efficiency of data processing and storage systems has become a key factor of various computing environments. This survey explores the transformative role of Non-Volatile Memory Express (NVMe) Solid-State Drives (SSDs) across different domains, including Big Data processing, Cloud Computing, High Performance Computing (HPC), and containerized applications. The motivation behind this comprehensive review is to understand how NVMe SSDs, known for …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 3, 2025 · pp. 01–21 Read article
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Role of Beowulf Clusters in Next-Generation Military Applications: A Comprehensive Study
Abstract: Beowulf clusters, which utilize cost-effective commodity hardware combined with open-source software for parallel computing, have emerged as a viable and efficient solution for high-performance computing needs. This paper explores their growing relevance and practical applications in modern and future military technologies. Contemporary military operations increasingly rely on rapid data processing, real-time intelligence, high-fidelity simulations, and autonomous decision-making systems. Beowulf clusters offer scalable and adaptable computational power that supports these demands …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 01–07 Read article
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Parallel Greedy Approach for Phylogenetic Tree Construction in the Context of Marine Species
Abstract: The rebuilding of phylogenetic trees for marine species shows major computing problems because of the massive genomic data and the huge biodiversity inherent in ocean ecosystems. Traditional phylogenetic methods are accurate but become more expensive when they are processing with thousands of marine taxa parallelly. This article shows a critical analysis of parallel greedy algorithms as an adaptable solution for large-scale marine phylogenetics. It examines the main principles of greedy …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 33–45 Read article
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Atmospheric Modeling: A Comprehensive Review of Numerical Approaches and Applications
Abstract: Atmospheric modeling plays a crucial role in understanding and predicting atmospheric processes, weather patterns, and climate variability. This review synthesizes current methodologies and applications across several types of atmospheric models, including numerical weather prediction (NWP), climate models, air quality models, and chemical transport models. We explore the intricacies of data assimilation, model evaluation, parameterization, and the importance of high-performance computing in advancing model accuracy and efficiency. Special emphasis is placed …
Published in International Journal of Atmosphere · Vol. 1, Issue 2, 2024 · pp. 16–21 Read article
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Application of Proportional-Share with Punishment Principle for Resource Sharing in Parallel Computing Applications
Abstract: Efficient resource sharing is a cornerstone of high-performance parallel computing. While proportional-share scheduling has long been a foundational approach for distributing resources according to predefined weights, its effectiveness can be compromised by tasks that over-consume their allocated share, leading to system-wide performance degradation and unfairness. This review article investigates the application of the “Proportional-Share with Punishment” (PSWP) principle, a hybrid scheduling paradigm designed to address this challenge. PSWP integrates the …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article
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Learning Data Structures: Key to Good Programming
Abstract: Data structures are the most crucial feature of good programming and are needed to solve hard computational problems. This model makes use of two different recurrent neural network architectures, specifically long short-term memory (LSTM), and gated recurrent unit (GRU) networks. It explains how selecting and using the correct data structures may speed up computations, optimize memory, and scale code. How data structures and algorithms relate and how to think about …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 29–39 Read article
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Implementing and Analyzing Network Commands in Cloud and Edge Computing Environments with Cisco Simulators
Abstract: The present review examines edge and cloud topologies and compares them according to latency. Instead of using distant data centers like cloud computing platforms, edge computing designs process data physically close to the source. Increased demand for Internet of Things (IoT) devices, which are growing more concerned with real-time data processing and analysis, has fueled the expansion of edge computing and cloud computing. In essence, each of these designs offers …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 62–69 Read article
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Advancements and Challenges in Computer Hardware Technology Management: Innovations, Performance, and Future Directions
Abstract: Modern computing systems depend on computer hardware technology for performance, efficiency, and innovation. Processing units, memory storage, input/output devices, and networking hardware are covered in this article. It emphasizes how multi-core processors, SSDs, and integrated circuits have increased computational power and speed. The essay also discusses quantum computing, edge computing, and the IoT, which will change hardware. Finally, the essay discusses hardware design challenges such power consumption, heat control, and …
Published in International Journal of Solid State Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 1–8 Read article
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Implementation of STATIC-RANDOM-ACCESS-MEMORY-Based In-Memory Computing-architecture for improving Energy Efficiency
Abstract: The in-memory-computing architecture the improvement of big data and high-performance computing. In memory-computing (IMC) as reduces the latency and power consumption of data processing. Proposed research paper static random-access memory-based IMC architecture. By completing internal write-back, NMOS transistors increase computational efficiency and eliminate the need to read the computational output right away. A 128×128 STATIC-RANDOM-ACCESS-MEMORY-IMC macro chip is designed using the 78-nm technology. The energy efficiency of 55.3TOPS/W with supply …
Published in Journal of VLSI Design Tools and Technology · Vol. 15, Issue 1, 2025 · pp. 25–35 Read article
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The AI Revolution: Transforming Business Decision-Making
Abstract: Industries undergo a transformation thanks to artificial intelligence, which makes machines capable of activities that previously required human intelligence. This interdisciplinary field of computer science models human thought processes, impacting sectors from autonomous vehicles to creative AI tools. Integrating AI into business operations transforms decision-making and enhances corporate performance. AI-driven methodologies analyze vast datasets to provide valuable insights and facilitate decisions beyond human capability. Predictive modeling anticipates consumer behavior, market …
Published in Journal of Electronic Design Technology · Vol. 15, Issue 2, 2024 · pp. 25–32 Read article
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Virtual Machine Cost & Computing comparison between cloud service
Abstract: Cloud computing has revolutionized enterprise IT infrastructure with virtual machines forming the cornerstone of Infrastructure as a Service deployment. This study provides a detailed comparative evaluation of virtual machine pricing and computational performance among three leading cloud computing platforms: Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). Through quantitative analysis of current pricing data from September 2025, independent performance benchmarks from Cockroach Labs 2021 Report, and market …
Published in International Journal of Mobile Computing Technology · Vol. 4, Issue 2, 2026 Read article
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Biomimicry of Eucalyptus Leaf Design for Optimization and Fabrication of Airfoil
Abstract: Biomimicry is the practice of drawing inspiration from natural forms to solve engineering problems, which has become progressively popular for refining design efficiency and performance. This work discovers how biomimicry can be applied to airfoil design, precisely through the unique structure of Eucalyptus leaves, a concept rarely explored in airfoil profiling. The work presented here, focuses on enhancing airfoil designs by incorporating the intricate features of these leaves. The airfoil …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 359–372 Read article
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A Physics-Informed Graph Neural Network Framework for Real- Time Thermal-Aware Fault Prediction and Adaptive Power Optimization in Heterogeneous System-on-Chip Architectures
Abstract: Heterogeneous System-on-Chip (SoC) architectures are increasingly adopted in edge computing, artificial intelligence, autonomous systems, and high-performance embedded platforms due to their superior computational efficiency and flexibility. However, increasing integration density and workload diversity introduce severe thermal hotspots, accelerated device degradation, and unexpected hardware faults that adversely affect system reliability and energy efficiency. This study proposes a Physics-Informed Graph Neural Network (PI-GNN) framework for real-time thermal- aware fault prediction and adaptive …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 2, 2026 Read article
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A Practical Approach for Privacy Preserving in Cloud Computing Using Fully Homomorphic Encryption Scheme BFV and CKKS
Abstract: Cloud computing is a new type of computing architecture whereby data may be accessed over the Internet along with other services linked to its scalable data centers in the cloud. The risk associated with computing is increased since it provides essential services that are typically provided to any third party, making it more difficult to enable data security, privacy, confidentiality, integrity, and authentication. To reduce security risks, most users choose …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 1, 2025 · pp. 1–8 Read article
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Proposed System: Quantum Computing Processor Based on Linear Number Relation
Abstract: This paper details the design and implementation of a specialized quantum processor tailored for efficiently evaluating custom mathematical formulas. Optimized to perform a specific set of arithmetic and logical operations, this processor delivers a stable and high-performance computing platform. Unlike general-purpose quantum processors, which are designed for versatility across a wide range of algorithms, this dedicated processor aims to enhance performance and accuracy for a targeted set of tasks. The …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 3, 2024 · pp. 24–32 Read article
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Deep Learning-Based Thermal Prediction Models for Solid-State Electronic Devices
Abstract: The rapid advancement of solid-state electronic devices in high-performance computing, communication systems, automotive electronics, and renewable energy applications has significantly increased concerns related to thermal management and device reliability. Excessive heat generation in semiconductor devices adversely affects operational efficiency, switching performance, lifespan, and overall system stability. Traditional thermal prediction methods often require complex numerical computations and extensive simulation time, making them less suitable for real-time monitoring and adaptive control applications. …
Published in International Journal of Solid State Innovations & Research · Vol. 4, Issue 1, 2026 Read article