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Implementing Global Memory Management in a Workstation Cluster

机译：在工作站群集中实施全局内存管理

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Advances in network and processor technology have greatly changed the communication and computational power of local-area workstation clusters. However, operating systems still treat workstation clusters as a collection of loosely-connected processors, where each workstation acts as an autonomous and independent agent. This operating system structure makes it difficult to exploit the characteristics of current clusters, such as low-latency communication, huge primary memories, and high-speed processors, in order to improve the performance of cluster applications. This paper describes the design and implementation of global memory management in a workstation cluster. Our objective is to use a single, unified, but distributed memory management algorithm at the lowest level of the operating system. By managing memory globally at this level, all system- and higher-level software, including VM, file systems, transaction systems, and user applications, can benefit from available cluster memory. We have implemented our algorithm in the OSF/1 operating system running on an ATM-connected cluster of DEC Alpha workstations. Our measurements show that on a suite of memory-intensive programs, our system improves performance by a factor of 1.5 to 3.5. We also show that our algorithm has a performance advantage over others that have been proposed in the past.
机译：网络和处理器技术的进步极大地改变了本地工作站集群的通信和计算能力。但是，操作系统仍将工作站群集视为松散连接的处理器的集合，其中每个工作站都充当自主和独立的代理。这种操作系统结构使得难以利用当前集群的特性，例如低延迟通信，巨大的主内存和高速处理器，以提高集群应用程序的性能。本文介绍了工作站群集中全局内存管理的设计和实现。我们的目标是在操作系统的最低级别使用单一，统一但分布式的内存管理算法。通过在此级别上全局管理内存，所有系统级和更高级别的软件（包括VM，文件系统，事务系统和用户应用程序）都可以从可用的群集内存中受益。我们已经在DEC Alpha工作站的ATM连接群集上运行的OSF / 1操作系统中实现了算法。我们的测量表明，在一组内存密集型程序上，我们的系统将性能提高了1.5到3.5倍。我们还表明，与过去提出的其他算法相比，我们的算法具有性能优势。

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