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/
Authors
- V. S. Shankar Sriram (ORCID: https://orcid.org/0000-0001-7870-7944)
- Nikhil Muralidhar (ORCID: https://orcid.org/0000-0001-7068-2981)
- Vishu Krishnamurthy
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