<![CDATA[The gap between increased processor speed and access to the main memory wall is a significant obstacle in the optimization of modern computing systems, where today's applications require processing large data with real-time responses. This study aims to analyze the effectiveness of the implementation of cache memory technology in improving the performance of modern computing systems, focusing on: 1) identification of key parameters that affect the effectiveness of cache on various workloads, 2) evaluation of adaptive cache replacement algorithms, 3) analysis of performance trade-offs with energy efficiency and security, and 4) formulation of optimal cache architecture recommendations. The research method uses a qualitative approach through a comprehensive literature study of 2020-2024 publications from the academic databases of IEEE Xplore, ACM Digital Library, Scopus, ScienceDirect, and SINTA with thematic content analysis and comparative evaluation of various cache technology implementations. The results showed that: the multi-level caching architecture increased system throughput by an average of 37.5%; adaptive algorithms such as RRIP increased hit rate by 23.7% compared to conventional LRU; SRAM/STT-MRAM hybrid technology saves up to 44.3% energy with minimal performance overhead; and the proposed integrated framework resulted in a 34.8% performance increase with a 27.5% reduction in energy consumption. Further research is recommended to implement and experimentally test the proposed framework on various computing platforms, develop more adaptive machine learning-based cache replacement algorithms, and explore the integration of cache technology with neuromorphic computing architectures.]]>
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