Enhancing Cache Performance Through FIFO replacement algorithm optimization for high-performance computing

Cache replacement algorithms are used to optimize the time taken for the central processing Unit (CPU) to process information by storing information needed by the processor at that time and possibly in future so that if the processor needs that information it can be provided immediately. There are a number of techniques (FIFO, LRU, CC, LFU, LRU, GDSF, MRU, Hybrid) that are easily used to organize information in such a way that the information needed by the CPU to remain busy and maintain its speed of processing is readily available. FIFO is known for its ease of implementation and low computational complexity. Therefore, this paper examines the scenarios in which FIFO fails and proposes techniques to enhance cache performance by optimizing FIFO through the integration of machine learning to predict future request and perform intelligent prefetching to preload relevant data into the cache. The machine learning approach increased the cache hit and increased the hit time.