AI-ASSISTED MEMORY AND CACHE OPTIMIZATION IN MODERN OPERATING SYSTEMS AND MULTICORE PROCESSORS

Memory and cache optimization are crucial in various areas of computing, including multicore processors and operating systems handling diverse workloads.Traditional memory management techniques such as Least Recently Used (LRU) and First-In First-Out (FIFO) are still widely used today.However, these methods do not adapt to changing workload patterns, resulting in inefficiencies such as increased cache misses and memory latency.Artificial Intelligence (AI) offers a promising solution to memory and cache management by dynamically adapting to workload variations, thereby enabling maximum resource utilization.Studies have shown that AI-based optimization can lead to a 40% reduction in memory latency, a 15-20% increase in cache hit rates, and lower energy consumption.These improvements make AI particularly well-suited for modern high-performance computing platforms.AI can enhance computational efficiency, eliminate bottlenecks, and improve system responsiveness.Future research should focus on real-time implementation of AI AI-Assisted Memory and Cache Optimization in Modern Operating Systems and Multicore Processors https://iaeme.com/Home/

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Publication Details

Journal
INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING & TECHNOLOGY
Published
2025-04-16
DOI
https://doi.org/10.34218/ijcet_16_02_018
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

AI-ASSISTED MEMORY AND CACHE OPTIMIZATION IN MODERN OPERATING SYSTEMS AND MULTICORE PROCESSORS

V. S. Shankar Sriram, Nikhil Muralidhar, Vishu Krishnamurthy
INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING & TECHNOLOGY
Parallel Computing and Optimization Techniques
article

AI-ASSISTED MEMORY AND CACHE OPTIMIZATION IN MODERN OPERATING SYSTEMS AND MULTICORE PROCESSORS

V. S. Shankar Sriram, Nikhil Muralidhar, Vishu Krishnamurthy
article en

Abstract

Memory and cache optimization are crucial in various areas of computing, including multicore processors and operating systems handling diverse workloads.Traditional memory management techniques such as Least Recently Used (LRU) and First-In First-Out (FIFO) are still widely used today.However, these methods do not adapt to changing workload patterns, resulting in inefficiencies such as increased cache misses and memory latency.Artificial Intelligence (AI) offers a promising solution to memory and cache management by dynamically adapting to workload variations, thereby enabling maximum resource utilization.Studies have shown that AI-based optimization can lead to a 40% reduction in memory latency, a 15-20% increase in cache hit rates, and lower energy consumption.These improvements make AI particularly well-suited for modern high-performance computing platforms.AI can enhance computational efficiency, eliminate bottlenecks, and improve system responsiveness.Future research should focus on real-time implementation of AI AI-Assisted Memory and Cache Optimization in Modern Operating Systems and Multicore Processors https://iaeme.com/Home/

INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING & TECHNOLOGYVol. 16(2)
Affordable and clean energy
Openalex Percentile: Top 94%
Parallel Computing and Optimization Techniques
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AI-ASSISTED MEMORY AND CACHE OPTIMIZATION IN MODERN OPERATING SYSTEMS AND MULTICORE PROCESSORS — V. S. Shankar Sriram, Nikhil Muralidhar, et al. · INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING & TECHNOLOGY (2025) | TGRS Research Map | TGRS