基于轮询的混合存储系统接口

Trung Le, Zhao Zhang, Zhichun Zhu
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引用次数: 1

摘要

现代传统的DRAM主存系统已不能满足当今数据密集型应用对容量和带宽日益增长的需求。非易失性存储器(Non-Volatile Memory, NVM)由于具有更高的存储密度和非易失性,作为基于dram的存储系统的替代方案得到了广泛的研究。混合存储系统受益于DRAM和NVM技术,但由于各种存储技术的不同时序要求和复杂的架构支持,传统的内存控制器(MC)无法有效地跟踪和调度异构系统中所有存储设备的操作。为了解决这个问题,我们提出了一个称为POMI的混合内存架构框架。它在每个DIMM上插入一个小的缓冲芯片,将操作调度与控制器解耦,从而支持系统中的各种存储技术。传统的基于内存的系统依赖于主MC来管理所有内存,而POMI使用基于轮询的内存总线协议进行通信,并解决内存模块之间的总线冲突。每个DIMM上的缓冲芯片将向主MC提供反馈信息,因此轮询开销是微不足道的。这有几个好处:技术无关的内存系统、更高的并行性和更好的可伸缩性。我们使用八核工作负载的实验结果表明,POMI可以有效地支持异构系统,并且在内存密集型工作负载下,它比混合内存系统的现有接口平均高出22.0%。
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POMI: Polling-Based Memory Interface for Hybrid Memory System
Modern conventional DRAM main memory system will no longer satisfy the growing demand for capacity and bandwidth on today’s data-intensive applications. Non-Volatile Memory (NVM) has been extensively researched as the alter-native for DRAM-based system due to its higher density and non-volatile characteristics. Hybrid memory system benefits from both DRAM and NVM technologies, however traditional Memory Controller (MC) cannot efficiently track and schedule operations for all the memory devices in heterogeneous systems due to different timing requirements and complex architecture supports of various memory technologies. To address this issue, we propose a hybrid memory architecture framework called POMI. It uses a small buffer chip inserted on each DIMM to decouple operation scheduling from the controller to enable the support for diverse memory technologies in the system. Unlike the conventional DRAM-based system, which relies on the main MC to govern all DIMMs, POMI uses polling-based memory bus protocol for communication and to resolve any bus conflicts between memory modules. The buffer chip on each DIMM will provide feedback information to the main MC so that the polling overhead is trivial. This gives several benefits: technology-independent memory system, higher parallelism, and better scalability. Our experimental results using octa-core workloads show that POMI can efficiently support heterogeneous systems and it outperforms an existing interface for hybrid memory systems by 22.0% on average for memory-intensive workloads.
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