Adaptive Migration Decision for Multi-Tenant Memory Systems

2025-05-14

AI Summary

To address the inefficiency caused by blind page migration in multi-tenant hierarchical memory systems, this paper proposes an adaptive page migration decision framework. The method introduces a novel, per-page “ping-pong” behavior–based dynamic migration-friendliness detection mechanism, enabling process-granularity control over migration initiation and suspension. It jointly models page hotness and migration patterns to support low-overhead, fine-grained runtime adaptation to access pattern changes. Implemented at the Linux kernel level and co-optimized with CXL hardware, the framework leverages hardware-assisted memory semantics for efficient decision-making. Evaluation on commercial CXL platforms demonstrates substantial reduction in spurious migrations: average memory latency decreases by 12.7% and bandwidth utilization improves by 19.3% across both single- and multi-tenant workloads.

Technology Category

• Machine Learning: Hardware-aware ML
• Cognitive Modeling & Cognitive Systems: Adaptive Behavior
• Data Mining & Knowledge Management: Scalability, Parallel & Distributed Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures
• User Modeling, Personalization and Recommendation: Federated recommendation systems and personalization
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Tiered memory systems consisting of fast small memory and slow large memory have emerged to provide high capacity memory in a cost-effective way. The effectiveness of tiered memory systems relies on how many memory accesses can be absorbed by the fast first-tier memory by page migration. The recent studies proposed several different ways of detecting hot pages and migrating them efficiently. However, our investigation shows that page migration is not always beneficial as it has the associated cost of detecting and migrating hot pages. When an application is unfriendly to migration, it is often better not to migrate pages at all. Based on the observation on migration friendliness, this paper proposes a migration control framework for multi-tenant tiered memory systems. First, it proposes a detection mechanism for migration friendliness, using per-page ping-pong status. Ping-pong pages which are promoted and demoted repeatedly in a short period of time tells migration effectiveness. Based on their change behaviors, migration is stopped or continued. After the page migration is stopped, the second mechanism detects changes of memory access patterns in a low cost way to determine whether migration needs to be resumed. Finally, as each application has a different behavior, our framework provides per-process migration control to selectively stop and start migration depending on application characteristics. We implement the framework in the Linux kernel. The evaluation with a commercial CXL-based tiered memory system shows that it effectively controls migration in single and multi-tenant environments.

Problem

• Determining migration friendliness of applications in tiered memory systems
• Controlling page migration based on access pattern changes
• Providing per-process migration control for multi-tenant environments

Innovation

• Detects migration friendliness using per-page ping-pong status
• Monitors memory access patterns to resume migration if needed
• Provides per-process migration control based on application behavior