Abstract

With the advantage of faster data access than traditional disks, in-memory database systems, such as Redis and Memcached, have been widely applied in data centers and embedded systems. The performance of in-memory database greatly depends on the access speed of memory. With the requirement of high bandwidth and low energy, die-stacked memory (e.g., High Bandwidth Memory (HBM)) has been developed to extend the channel number and width. However, the capacity of die-stacked memory is limited due to the interposer challenge. Thus, hybrid memory system with traditional Dynamic Random Access Memory (DRAM) and die-stacked memory emerges. Existing works have proposed to place and manage data on hybrid memory architecture in the view of hardware. This paper considers to manage in-memory database data in hybrid memory in the view of application. We first perform a preliminary study on the hotness distribution of client requests on Redis. From the results, we observe that most requests happen on a small portion of data objects in in-memory database. Then, we propose the Application-oriented Data Migration called ADM to accelerate in-memory database on hybrid memory. We design a hotness management method and two migration policies to migrate data into or out of HBM. We take Redis under comprehensive benchmarks as a case study for the proposed method. Through the experimental results, it is verified that our proposed method can effectively gain performance improvement and reduce energy consumption compared with existing Redis database.

Highlights

  • In this paper we focus on exploring an efficient application-level migration policy for in-memory database systems that executes hybrid memory systems with flat memory organization

  • We propose an Application-oriented Data Migration method called ADM to accelerate the in-memory database based on hybrid memory architecture

  • Data objects are exclusively stored in HBM or Dynamic Random Access Memory (DRAM) address space, i.e., two memories are in flat address space and there is only one copy for each data object of in-memory database

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Summary

Introduction

With the vigorous development of cloud computing and Internet technologies, a large number of emerging applications with high concurrency and low latency have emerged. How to place and migrate data between two types of memories is mostly studied to optimize performance and energy efficiency. We consider in-memory database data management on hybrid memory system in the view of application. In this paper we focus on exploring an efficient application-level migration policy for in-memory database systems that executes hybrid memory systems with flat memory organization. We observe that a large portion of requests happen on a small amount of data objects, which indicates the characteristics of hot data By exploiting this observation, we propose an Application-oriented Data Migration method called ADM to accelerate the in-memory database based on hybrid memory architecture. The key idea is to migrate hot data objects in the database to HBM die-stacked memory for high bandwidth.

Background and Motivation
In-Memory Database
Motivation and Scope of This Paper
Overview
HBM Migr-In
HBM Migr-Out
Implementation of ADM
Experiment and Evaluation
Experimental Setup
Behaviours of Object Migration
Performance and Energy Results
Sensitivity to Data Size Range
Sensitivity to Set-Get Operation Ratio
Findings
Conclusions and Futuer Work
Full Text
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