Memory Management Issues in Large Scale Shared Memory MIMD Multiprocessors

大规模共享内存 MIMD 多处理器中的内存管理问题

• 批准号: 9113170
• 负责人: Carla Ellis
• 金额: $ 24.5万
• 依托单位: Duke University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1992
• 资助国家: 美国
• 起止时间: 1992-02-15 至 1994-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9113170&HistoricalAwards=false
• 关键词: Memory; Management; Issues; Large; Scale

Nonuniformity of memory access is an almost inevitable feature of the memory architecture in shared memory designs that can scale to large numbers of processors, creating the increasingly important class of NUMA (nonuniform memory access time) multiprocessors. Managing the placement and movement of code and data is crucial to performance in NUMA architectures. This has been called the NUMA Problem. The I/O bottleneck problem is also exacerbated by parallel architectures which widen the gap between processing speed and disk speed even beyond that created by improved processor technology. This project investigates operating system mechanisms and policies for the management of the various levels of shared storage in such large- scale shared memory multiprocessors. The specific projects divide into the following classes: main memory management (both traditional virtual memory and the migration and replication of pages among various main memory modules), parallel file system design, workload characterization and performance evaluation methodology and the role of the programming environment in solving the NUMA Problem.

内存访问的不均匀性是共享内存设计中内存架构几乎不可避免的特征，可以扩展到大量处理器，从而创建越来越重要的 NUMA（非均匀内存访问时间）多处理器类别。 管理代码和数据的放置和移动对于 NUMA 架构的性能至关重要。 这被称为 NUMA 问题。 并行架构也加剧了 I/O 瓶颈问题，并行架构扩大了处理速度和磁盘速度之间的差距，甚至超出了改进的处理器技术所造成的差距。 该项目研究用于管理此类大规模共享内存多处理器中的各级共享存储的操作系统机制和策略。 具体项目分为以下几类：主存管理（包括传统的虚拟内存和各个主存模块之间页面的迁移和复制）、并行文件系统设计、工作负载表征和性能评估方法以及编程环境在解决NUMA问题中的作用。