Intelligent Hybrid Memory Scheduling Based on Page Pattern Recognition

Hybrid memory systems exhibit disparities in their heterogeneous memory components' access speeds. Dynamic page scheduling to ensure memory access predominantly occurs in the faster memory components is essential for optimizing the performance of hybrid memory systems. Recent works attempt to optimize page scheduling by predicting their hotness using neural network models. However, they face two crucial challenges: the page explosion problem and the new pages problem. We propose an intelligent hybrid memory scheduler driven by page pattern recognition to address these two challenges. Experimental results demonstrate that our approach outperforms state-of-the-art intelligent schedulers regarding effectiveness and cost.