Abstract
Cache memory plays a vital role in improving computer system performance by reducing the speed gap between the processor and main memory. This study provides a comparative analysis of various cache memory optimization techniques, including cache replacement policies, mapping methods, multi-level cache architectures, prefetching, and cache partitioning. Using a literature-based approach, the research reviews and evaluates findings from existing studies and scholarly publications. Results indicate that techniques such as Least Recently Used (LRU) policies improve hit rates by 10-25% compared to FIFO, while set-associative mapping reduces miss rates by 15-30% relative to direct mapping. Multi-level cache reduces average memory access latency by up to 50%, and prefetching can boost performance by 20-40% in data-intensive workloads. This study provides a concise overview of cache optimization techniques and their impact on system performance, contributing to a better understanding of cache memory design in modern computer architectures.
Keywords: Cache Memory Optimization, Computer Architecture, Cache Replacement Policy, Cache Mapping
| Journal | International Journal of Research and Innovation in Social Science |
|---|---|
| ISSN | 2454-6186 |
| Volume / Issue | Volume 10 , Issue 8 |
| Pages | pp. 121-125 |
| Year | 2026 |
| DOI | 10.47772/IJRISS.2026.100800010 |
| Publisher | RSIS International |
| License | Open Access |