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13 articles for “compiler optimization”
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Automating Compiler Optimization: A Machine Learning Approach
Abstract: This study reports on an ML-based approach to compiler optimization, complementing traditional optimization methods that rely strongly on hand-tuned settings. Compiler optimization plays a key role in performance-speedup and energy optimization of complex contemporary software systems. However, the traditional approach to optimizer settings involves laborious, error-prone, and scale-insensitive human-in-the-loop intervention, especially in the complex and high-demand environments in which today's computing application thrives. By integrating RL and GA, we can …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 12–16 Read article
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Educating Compilers to Learn: Utilizing Machine Learning for More Brilliant Code Optimization
Abstract: This study explores the use of machine learning (ML) approaches to compiler optimization. The now-traditional static compilation techniques are transformed into adaptive, dynamic systems capable of making context-specific advancements. Traditional compilers rely mostly on heuristic or rule-based optimization techniques. While these techniques work well in general cases, they consistently fail to adapt well within the limits of code structures that modern machines display. This limitation is especially acute in today's …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 50–54 Read article
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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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RTL-to-GDSII Flow Optimization for Low-Power 32-bit RISC-V Processor
Abstract: This paper presents the implementation and optimization of a 32-bit RISC-V processor, transitioning from Register Transfer Level (RTL) design to final GDSII using Synopsys Fusion Compiler over 32nm technology node. The processor architecture is based on the RV32I base instruction set and incorporates a 5-stage pipeline to achieve a balanced trade-off between performance and design complexity. The design methodology involved RTL synthesis, gate-level netlist generation, and successive physical design stages …
Published in Journal of VLSI Design Tools and Technology · Vol. 15, Issue 3, 2025 · pp. 1–10 Read article
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Efficient Gabor Filter Design Using Verilog HDL with Multiplier-accumulator (MAC) Implementation
Abstract: This paper introduces a novel and enhanced Gabor filter design aimed at addressing the demands of image processing applications using the Verilog Hardware Description Language (HDL). Specifically, it leverages the Reconstruct Gabor filter technique to elevate the performance and quality of standard image outputs. The primary objective of this research endeavor is to simplify the study, conduct an in-depth analysis, and substantially enhance the design's efficiency, all while ensuring the …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 1, Issue 2, 2023 · pp. 40–46 Read article
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Comparative Analysis of Modern Programming Paradigms: Evaluating Language Efficiency and Compiler Design Technique
Abstract: This paper attempts to provide some insights into the efficiency of modern programming paradigms via a comparative study and explore the important role played by compiler design in the optimization of these languages. Programming languages have been evolving quickly over time and different paradigms: imperative, functional, or object-oriented programming come with their idiosyncrasies and optimization techniques. The study starts by defining the foundational principles of each paradigm. It then goes …
Published in Recent Trends in Programming languages · Vol. 11, Issue 3, 2024 · pp. 1–9 Read article
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Revolutionizing Anti-Allergy Medications: A Comprehensive Review of Target Discovery and Medicinal Chemistry
Abstract: Above the past few decades, the prevalence of allergy illnesses has been steadily rising, impacting 20–30% of the world's population. Multiple targets are involved in allergic reactions to infections of the skin, digestive tract, and respiratory system. Developing medications with a good curative efficacy and minimal side effects while utilizing novel multi-targets and processes in accordance with the clinical features of various allergic populations and allergens is the primary challenge …
Published in International Journal of Advance in Molecular Engineering · Vol. 1, Issue 1, 2023 · pp. 49–54 Read article
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AI-Driven Multi-Objective Optimization of Conductive Polymer Composites for High-Performance Flexible Electronics
Abstract: The development of conductive polymer composites (CPCs) is critical for advancing flexible and wearable electronic technologies. However, the conventional trial-and-error approach to material formulation is time-consuming and often inefficient due to the high-dimensional nature of the design space. This study introduces a novel AI-driven framework that integrates machine learning (ML) with multi-objective optimization to accelerate the discovery of high-performance CPCs. A dataset of 1,000 experimentally reported formulations was compiled, capturing …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 734–745 Read article
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Money Laundering Transaction with Machine Learning
Abstract: This study discusses the use of machine learning algorithms to discover firms that are prone to money laundering. The purpose of this research is to develop, describe, and test a machine learning model for determining which bank transactions should be physically scrutinized for money laundering activities. To train a supervised machine learning model, three categories of historical data are required: legitimate "normal" transactions, transactions flagged as suspicious by the bank's …
Published in Current Trends in Information Technology · Vol. 14, Issue 2, 2024 · pp. 1–15 Read article
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A Review on Transforming Patient Pathways: The Impact of Pharmaceutical Software on Drug Manufacturing and Safety Monitoring
Abstract: The development, production, and safety monitoring of pharmaceuticals are being revolutionized by incorporating digital technologies. Throughout drug lifecycles, pharmaceutical software which includes cloud-based systems, automation, data analytics, and artificial intelligence (AI) has emerged behind efficiency and innovation. Real-time monitoring, predictive maintenance, and process optimization are made possible in manufacturing by software tools like Digital Twins, Manufacturing Execution Systems (MES), and Quality Management Systems (QMS). These technologies improve batch consistency, lower …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 1, 2026 · pp. 40–46 Read article
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Comparative Study of the Mechanical and Durability Performance of Interlocking Concrete Pavement Blocks
Abstract: Interlocking concrete pavement blocks (ICPBs) have emerged as a durable, modular, and sustainable alternative to traditional pavement systems. Their performance depends heavily on the mechanical characteristics of the concrete mix, block geometry, compaction technique, and curing conditions. This review compiles and analyzes research findings related to the strength, durability, structural behavior, and long-term performance of ICPBs produced using traditional and modified concrete mixes. Key parameters evaluated include compressive strength, split …
Published in Trends in Transport Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 24–30 Read article
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Mechanical Strength Prediction of Nano-Silica Concrete Composites Using Machine Learning Techniques
Abstract: Nano-silica, or nanosilica, refers to silicon dioxide nanoparticles, which are a kind of silica (SiO₂) with diameters that often fall below 100 nanometers. This nanomaterial has attracted considerable attention because of its distinctive characteristics and diverse array of uses, notably in augmenting the performance of materials such as concrete. The integration of nanoparticles with cementitious matrix in nano-silica concrete offers a viable approach to improving the mechanical characteristics and longevity …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 963–973 Read article
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Therapeutic Potential of Terminalia arjuna Bark in the Management of Hemorrhoids: A Comprehensive Review
Abstract: Background: Hemorrhoids appear frequently among anorectal disorders since they create vascular swelling together with pain symptoms, while leading to bleeding and mucosal tissue tending to slide out. Though effective therapy exists, traditional treatments produce various adverse effects and lead to recurrence and inconsistent patient following of medical recommendations over the long term. Plantbased therapeutic medicines have gained rising demand, which leads experts to investigate medicinal plants with established pharmacological effects. …
Published in Research & Reviews: A Journal of Pharmacognosy · Vol. 12, Issue 2, 2025 · pp. 22–32 Read article