The growing scale of data requires efficient memory subsystems with large memory capacity and high memory performance. Disaggregated architecture has become a promising solution for today's cloud and edge computing for its scalability and elasticity. As a critical part of disaggregation, disaggregated memory faces many design challenges in many dimensions, including hardware scalability, architecture structure, software system design, application programmability, resource allocation, power management, etc. These challenges inspire a number of novel solutions at different system levels to improve system efficiency. In this paper, we provide a comprehensive review of disaggregated memory, including the methodology and technologies of disaggregated memory system foundation, optimization, and management. We study the technical essentials of disaggregated memory systems and analyze them from the hardware, architecture, system, and application levels. Then, we compare the design details of typical cross-layer designs on disaggregated memory. Finally, we discuss the challenges and opportunities of future disaggregated memory works that serve better for next-generation elastic and efficient datacenters.

翻译：数据规模的不断增长要求内存子系统具备大容量与高性能。解耦架构因其可扩展性与弹性优势，已成为当前云计算与边缘计算领域的重要解决方案。作为解耦架构的核心组成部分，解耦内存在硬件可扩展性、体系结构、软件系统设计、应用可编程性、资源分配及功耗管理等多个维度面临诸多设计挑战。这些挑战催生了不同系统层级中诸多提升系统效率的创新方案。本文对解耦内存技术进行了系统性综述，涵盖解耦内存系统基础、优化与管理的方法论与技术体系。我们从硬件、架构、系统及应用层面剖析了解耦内存系统的技术要素，并对典型的解耦内存跨层设计方案进行了细节比较。最后，本文探讨了未来解耦内存研究面临的挑战与机遇，以期为构建更具弹性与高效的下一代数据中心提供支撑。