Collaborative Research: FoMR: Enabling High Instructions-per-Cycle (IPC) Counts in Future Multi-NUMA (Non Uniform Memory Access) Systems

合作研究：FoMR：在未来的多 NUMA（非均匀内存访问）系统中实现高每周期指令 (IPC) 计数

• 批准号: 2011212
• 负责人: Jishen Zhao
• 金额: $ 14万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-15 至 2024-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2011212&HistoricalAwards=false
• 关键词: Collaborative; Research; FoMR; Enabling; Instructions

Emerging memory technologies, such as three-dimensional die-stacked dynamic random access memory (3D-DRAM) and non-volatile random-access memory (NVRAM), introduce promising opportunities in achieving high performance for computer processors. Computer servers with mixed memory technologies introduce a new multi-dimensional non-uniform memory access (“multi-NUMA”) method, where the computer memory hierarchy has widely varying performance and efficiency characteristics depending on the type of memory and where it resides in the system. Despite the promising benefits, multi-NUMA systems impose significant architecture design challenges due to the level of heterogeneity they introduce. The multi-dimensional heterogeneity, which ranges from access latency, bandwidth, and access granularity to reliability and functionality, makes memory hierarchy performance and access behavior difficult to predict and manipulate. Addressing these issues can influence the architecture design for building efficient multi-NUMA systems and also spawn new applications that can deal with larger volumes of heterogeneous data than what is possible at present.This project aims to improve the performance of future server systems that incorporate mixed memory technologies. To achieve the objective, this project consists of three phases. The first phase seeks to reinvestigate the basic performance models, assumptions, and metrics of memory hierarchy architecture design, across memory system performance, reliability, and scalability, by encompassing the multi-NUMA scenario. Guided by the multi-NUMA-aware architecture design strategies, the second phase will focus on reconsidering the design of memory hierarchy architecture components that are critical to the application’s instructions-per-cycle (IPC) performance. Finally, the third phase seeks to ensure scalable IPC performance in both multi-socket and memory-fabric-based multi-NUMA systems.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

三维芯片堆叠动态随机存取存储器 (3D-DRAM) 和非易失性随机存取存储器 (NVRAM) 等新兴存储器技术为采用混合存储器技术的计算机处理器实现高性能带来了广阔的前景。引入了一种新的多维非均匀内存访问（“multi-NUMA”）方法，其中计算机内存层次结构具有广泛不同的性能和效率特征，具体取决于内存的类型及其在系统中的位置，尽管有很大的好处。 ,多 NUMA 系统由于引入的异构性水平（从访问延迟、带宽、访问数量到可靠性和功能）带来了重大的架构粒度设计挑战，使得内存层次结构性能和访问行为难以实现。解决这些问题可以影响构建多 NUMA 系统的架构设计，并催生高效的新应用程序，这些应用程序可以处理比目前更大量的异构数据。该项目旨在提高未来服务器的性能。结合混合内存技术的系统。为了实现这一目标，该项目由三个阶段组成，第一阶段旨在通过涵盖多 NUMA 场景，重新研究内存层次架构设计的基本性能模型、假设和指标，涵盖内存系统性能、可靠性和可扩展性。在多 NUMA 感知架构设计策略的指导下，第二阶段将重点重新考虑对应用程序的每周期指令 (IPC) 性能至关重要的内存层次架构组件的设计。在多插槽和基于内存结构的多 NUMA 系统中实现可扩展的 IPC 性能。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

SubZero: zero-copy IO for persistent main memory file systems

SubZero：持久主内存文件系统的零拷贝 IO

• DOI: 10.1145/3409963.3410489
• 发表时间: 2020-08
• 期刊: ACM SIGOPS Asia-Pacific Workshop on Systems (APSys
• 作者: Kim, Juno;Soh, Yun Joon;Izraelevitz, Joseph;Zhao, Jishen;Swanson, Steven
• 通讯作者: Swanson, Steven

NVLeak: Off-Chip Side-Channel Attacks via Non-Volatile Memory Systems

NVLeak：通过非易失性内存系统进行片外侧通道攻击

• 发表时间: 2023-01
• 期刊: USENIX Security
• 作者: Zixuan Wang; Mohammadkazem Taram
• 通讯作者: Mohammadkazem Taram

PMShifter: Enabling Persistent Memory Fluidness in Linux

PMShifter：在 Linux 中实现持久内存流动性

• DOI: 10.1145/3546591.3547523
• 发表时间: 2022-01
• 期刊: ACM Asia-Pacific Workshop on Systems (APSys
• 作者: Theodore Michailidis; Steven Swanson
• 通讯作者: Steven Swanson

Enabling Efficient Large-Scale Deep Learning Training with Cache Coherent Disaggregated Memory Systems

利用缓存一致性分解内存系统实现高效的大规模深度学习训练

• DOI: 10.1109/hpca53966.2022.00018
• 发表时间: 2022-04-01
• 期刊: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA)
• 作者: Zixuan Wang;Joonseop Sim;Euicheol Lim;Jishen Zhao
• 通讯作者: Jishen Zhao

Characterizing and Modeling Non-Volatile Memory Systems

非易失性存储系统的表征和建模

• DOI: 10.1109/micro50266.2020.00049
• 发表时间: 2020-10
• 期刊: IEEE/ACM International Symposium on Microarchitecture (MICRO
• 作者: Wang, Zixuan;Liu, Xiao;Yang, Jian;Michailidis, Theodore;Swanson, Steven;Zhao, Jishen
• 通讯作者: Zhao, Jishen