An Operating System Level Data Migration Scheme in Hybrid DRAM-NVM Memory Architecture

TL;DR

This paper introduces an OS-level data migration scheme for hybrid DRAM-NVM memory systems that reduces power consumption significantly by intelligently managing data movement based on workload characteristics.

Contribution

It proposes a novel data migration scheme using LRU queues at the OS level that considers performance and power impacts, addressing gaps in existing hybrid memory management.

Findings

Power consumption reduced by up to 79% compared to DRAM-only systems.

Migration scheme prevents unnecessary data movements, improving efficiency.

Workload characterization enables targeted and beneficial data migrations.

Abstract

With the emergence of Non-Volatile Memories (NVMs) and their shortcomings such as limited endurance and high power consumption in write requests, several studies have suggested hybrid memory architecture employing both Dynamic Random Access Memory (DRAM) and NVM in a memory system. By conducting a comprehensive experiments, we have observed that such studies lack to consider very important aspects of hybrid memories including the effect of: a) data migrations on performance, b) data migrations on power, and c) the granularity of data migration. This paper presents an efficient data migration scheme at the Operating System level in a hybrid DRAMNVM memory architecture. In the proposed scheme, two Least Recently Used (LRU) queues, one for DRAM section and one for NVM section, are used for the sake of data migration. With careful characterization of the workloads obtained from PARSEC benchmark suite, the proposed scheme prevents unnecessary migrations and only allows migrations which benefits the system in terms of power and performance. The experimental results show that the proposed scheme can reduce the power consumption up to 79% compared to DRAM-only memory and up to 48% compared to the state-of-the art techniques.