CSR: Large: Storage Class Memory Architecture for Energy Efficient Data Centers

到2011年，美国的数据中心将消耗约1000亿千瓦的能源，其中一半用于服务器。大部分功耗将从处理器转移到主存。 该项目不单纯依赖DRAM，而是采用多种技术为虚拟化计算机服务器构建一个高容量、高能效的存储系统，采用新的存储类存储器架构，融合了DRAM、相变存储器（PRAM）和Flash等多种存储技术。该项目雄心勃勃，在设计和开发高能效计算机服务器方面做出了基础性和应用性贡献。基本的贡献包括：一个新的集成内存架构，无缝管理混合内存资源;新的算法和能源，性能和耐力管理的政策;更好地了解管理程序？的作用，在资源管理和它的互动与上下系统层，以及一个新的混合DRAM和PRAM主存储器控制器。应用的贡献是将开发和传播的工具，包括模拟，分析模型和实际的软件/模拟硬件系统的形式。这项研究代表了一种新的“绿色计算技术”，它满足了未来计算系统的需求（例如，云计算、服务器场、商用计算机）。该项目通过研究机会和行业实习对本科生和研究生产生影响，旨在从计算机科学和计算机工程领域代表性不足的群体中招募人员。

By 2011, data centers in the U.S. are poised to consume around 100 billion KW of energy, half of which in servers. The majority of power consumption will shift from the processor to main memory. This project, rather than relying solely on DRAM, uses multiple technologies to construct a high-capacity, energy-efficient memory system for virtualized computer servers with a new Storage Class Memory Architecture that incorporates multiple memory technologies such as DRAM, Phase-change memory (PRAM) and Flash.This project is ambitious with fundamental and applied contributions in the design and development of energy-efficient computer servers. The fundamental contributions include: a new integrated memory architecture that seamlessly manages hybrid memory resources; novel algorithms and policies for energy, performance and endurance management; better understanding of the hypervisor?s role in resource management and its interaction with upper and lower system layers; and a new hybrid DRAM and PRAM main memory controller. The applied contribution is in the form of tools that will be developed and disseminate, including simulations, analytic models and actual software/emulated hardware system. This research represents a new "green computing technology" that satisfies the demands of future computing systems (e.g., cloud computing, server farms, commodity computers) in an exceptionally low energy manner. The project impacts undergraduate and graduate students through research opportunities and industry internships and aims to recruit people from under-represented groups in computer science and computer engineering.