Latency-Aware and Auto-Migrating Page Tables for ARM NUMA Servers

The non-uniform memory access (NUMA) architecture is the de facto norm in modern server processors. Applications running on NUMA processors may suffer significant performance degradation (NUMA effect) due to the non-uniform memory accesses, including data and page table accesses. Recent studies show that the NUMA effect of long-running memory-intensive workloads can be mitigated by replicating or migrating page tables to nodes that require accesses to remote page tables. However, this technique cannot adapt to the situation where other applications compete for the memory controller. Furthermore, it was only implemented on x86 processors and cannot be readily applied on ARM server processors, which are becoming increasingly popular. To address this issue, we designed the page table access latency aware (PTL-aware) page table auto-migration (Auto-PTM) mechanism. Then we implemented it on Linux ARM64 (the Linux kernel name for AArch64) by identifying the differences between the ARM architecture and the x86 architecture in terms of page table structure and the implementation of the Linux kernel source code. We evaluate it on real ARM NUMA servers. The experimental results demonstrate that, compared to the state-of-the-art PTM mechanism, our PTL-aware mechanism significantly enhances the performance of workloads in various scenarios (e.g., GUPS by 3.53x, XSBench by 1.77x, Hashjoin by 1.68x).

Authors

Institutions

Publication Details

Journal
Electronics
Published
2025-04-21
DOI
https://doi.org/10.3390/electronics14081685
Citations
1
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
2.27
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Latency-Aware and Auto-Migrating Page Tables for ARM NUMA Servers

Hongliang Qu, Peng Wang
1 citations
Electronics
Parallel Computing and Optimization Techniques
2.27
article

Latency-Aware and Auto-Migrating Page Tables for ARM NUMA Servers

Hongliang Qu, Peng Wang
article en
1 citations

Abstract

The non-uniform memory access (NUMA) architecture is the de facto norm in modern server processors. Applications running on NUMA processors may suffer significant performance degradation (NUMA effect) due to the non-uniform memory accesses, including data and page table accesses. Recent studies show that the NUMA effect of long-running memory-intensive workloads can be mitigated by replicating or migrating page tables to nodes that require accesses to remote page tables. However, this technique cannot adapt to the situation where other applications compete for the memory controller. Furthermore, it was only implemented on x86 processors and cannot be readily applied on ARM server processors, which are becoming increasingly popular. To address this issue, we designed the page table access latency aware (PTL-aware) page table auto-migration (Auto-PTM) mechanism. Then we implemented it on Linux ARM64 (the Linux kernel name for AArch64) by identifying the differences between the ARM architecture and the x86 architecture in terms of page table structure and the implementation of the Linux kernel source code. We evaluate it on real ARM NUMA servers. The experimental results demonstrate that, compared to the state-of-the-art PTM mechanism, our PTL-aware mechanism significantly enhances the performance of workloads in various scenarios (e.g., GUPS by 3.53x, XSBench by 1.77x, Hashjoin by 1.68x).

ElectronicsVol. 14(8)
Chinese Academy of Sciences (CN), Inspur (China) (CN), Shenzhen Institutes of Advanced Technology (CN), University of Chinese Academy of Sciences (CN)
Openalex Percentile: Top 16%
Parallel Computing and Optimization Techniques
2.27
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Latency-Aware and Auto-Migrating Page Tables for ARM NUMA Servers — Hongliang Qu, Peng Wang · Electronics (2025) | TGRS Research Map | TGRS