A hybrid memory architecture supporting fine-grained data migration

IF 3.4 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Frontiers of Computer Science Pub Date : 2024-01-22 DOI:10.1007/s11704-023-2675-y
Ye Chi, Jianhui Yue, Xiaofei Liao, Haikun Liu, Hai Jin
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Abstract

Hybrid memory systems composed of dynamic random access memory (DRAM) and Non-volatile memory (NVM) often exploit page migration technologies to fully take the advantages of different memory media. Most previous proposals usually migrate data at a granularity of 4 KB pages, and thus waste memory bandwidth and DRAM resource. In this paper, we propose Mocha, a non-hierarchical architecture that organizes DRAM and NVM in a flat address space physically, but manages them in a cache/memory hierarchy. Since the commercial NVM device-Intel Optane DC Persistent Memory Modules (DCPMM) actually access the physical media at a granularity of 256 bytes (an Optane block), we manage the DRAM cache at the 256-byte size to adapt to this feature of Optane. This design not only enables fine-grained data migration and management for the DRAM cache, but also avoids write amplification for Intel Optane DCPMM. We also create an Indirect Address Cache (IAC) in Hybrid Memory Controller (HMC) and propose a reverse address mapping table in the DRAM to speed up address translation and cache replacement. Moreover, we exploit a utility-based caching mechanism to filter cold blocks in the NVM, and further improve the efficiency of the DRAM cache. We implement Mocha in an architectural simulator. Experimental results show that Mocha can improve application performance by 8.2% on average (up to 24.6%), reduce 6.9% energy consumption and 25.9% data migration traffic on average, compared with a typical hybrid memory architecture–HSCC.

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支持细粒度数据迁移的混合内存架构
由动态随机存取存储器(DRAM)和非易失性存储器(NVM)组成的混合存储器系统通常利用页面迁移技术来充分利用不同存储器介质的优势。以前的大多数建议通常以 4 KB 页面的粒度迁移数据,因此浪费了内存带宽和 DRAM 资源。在本文中,我们提出了一种非分层架构--Mocha,它将 DRAM 和 NVM 组织在一个扁平的物理地址空间中,但将它们管理在一个高速缓存/内存分层中。由于商用 NVM 设备--英特尔 Optane DC 持久内存模块(DCPMM)实际上以 256 字节(一个 Optane 块)的粒度访问物理介质,因此我们以 256 字节的大小管理 DRAM 缓存,以适应 Optane 的这一特性。这种设计不仅实现了 DRAM 缓存的细粒度数据迁移和管理,还避免了英特尔 Optane DCPMM 的写放大。我们还在混合内存控制器(HMC)中创建了间接地址缓存(IAC),并在 DRAM 中提出了反向地址映射表,以加快地址转换和缓存替换。此外,我们还利用基于实用程序的缓存机制来过滤 NVM 中的冷块,并进一步提高 DRAM 缓存的效率。我们在架构模拟器中实现了 Mocha。实验结果表明,与典型的混合内存架构--HSCC 相比,Mocha 可以将应用性能平均提高 8.2%(最高可达 24.6%),平均降低 6.9% 的能耗和 25.9% 的数据迁移流量。
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来源期刊
Frontiers of Computer Science
Frontiers of Computer Science COMPUTER SCIENCE, INFORMATION SYSTEMS-COMPUTER SCIENCE, SOFTWARE ENGINEERING
CiteScore
8.60
自引率
2.40%
发文量
799
审稿时长
6-12 weeks
期刊介绍: Frontiers of Computer Science aims to provide a forum for the publication of peer-reviewed papers to promote rapid communication and exchange between computer scientists. The journal publishes research papers and review articles in a wide range of topics, including: architecture, software, artificial intelligence, theoretical computer science, networks and communication, information systems, multimedia and graphics, information security, interdisciplinary, etc. The journal especially encourages papers from new emerging and multidisciplinary areas, as well as papers reflecting the international trends of research and development and on special topics reporting progress made by Chinese computer scientists.
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