The evolving memory landscape for larger capacity prompts alternative approaches due to scalability challenges in multi-level page tables, which require multiple serial memory accesses for address translation. Hashed Page Tables (HPTs) have gained attention for ideally facilitating a single memory access per translation. However, current HPTs increase minor page fault latency, thereby impeding its superiority over conventional multi-level page table design. This paper provides a comprehensive analysis of HPTs regarding minor page fault latency concerning memory management subsystems. In particular, we demonstrate how feasibility issues in memory management with HPTs can escalate minor page fault latency. We observe that different page types in HPTs (anon pages and page caches) exhibit distinct behaviors on the occurrence of minor page faults, indicating a significant correlation between page types and minor page faults. To address these challenges, we proposeHashScape, a scheme that harmonizes with memory management using tailored HPTs per segment and size-tailored allocation via Virtual Memory Areas. Our evaluation demonstrates that HashScape significantly improves the insertion latency, with average, 95th, and 99thpercentiles improving by 1.8$\boldsymbol{\times}$, 1.9$\boldsymbol{\times}$, and 2.2$\boldsymbol{\times}$, respectively, resulting in an overall 10% reduction in minor page fault latency compared to a state-of-the-art HPT design.

Heterogeneous multicore systems have emerged as a promising approach to scale performance in high-end desktops within limited power and die size constraints. Despite their advantages, these systems face three major challenges: memory bandwidth limitation, shared cache contention, and heterogeneity. Small cores in these systems tend to occupy a significant portion of shared LLC and memory bandwidth, despite their lower computational capabilities, leading to performance degradation of up to 18% in memory-intensive workloads. Therefore, it is crucial to address these challenges holistically, considering shared resources and core heterogeneity while managing shared cache and bandwidth.