Penerapan Virtual Memory terhadap Kinerja CPU, GPU, dan Respons Multitasking pada Windows 10 - Fauzia Fredella; Ulya Rahman (Asosiasi Riset Teknik Elektro dan Informatika Indonesia, 2025)
The limitation of physical memory (RAM) is a primary constraint hindering optimal performance in modern operating systems, especially when running large applications or performing intensive multitasking, often resulting in crashes and high latency. This research aims to quantitatively analyze the effectiveness of Virtual Memory (VM) implementation as a solution to this RAM constraint on the Windows 10 operating system, focusing on VM’s impact on CPU performance, GPU performance, and multitasking response. The methodology employed is a controlled experiment using industry-standard benchmarks: Cinebench R20 (CPU), Unigine Heaven (GPU), and response time measurements in intensive multitasking scenarios. Experimental results demonstrate that VM activation improves CPU/GPU performance by up to 5% and accelerates multitasking response time by up to 15%, confirming VM's effectiveness in mitigating memory bottlenecks. Nevertheless, this study also identifies potential performance overhead stemming from excessive paging and swapping processes, which trigger the phenomenon of Thrashing. Therefore, the research recommends a dual optimization strategy to achieve maximum and stable performance: software optimization via the Least Recently Used (LRU) algorithm to suppress page faults, supported by hardware optimization including the use of an SSD for the swap file and increased RAM capacity.