利用标准核心技术以编程方式构建Linux集群设备

M. Katz, P. Papadopoulos, Greg Bruno
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引用次数: 30

摘要

集群已经实现了从实验室原型到成熟的生产计算平台的飞跃。随着32-128节点集群在科学实验室中的普及,这些机器的数量变化和专门配置正在急剧增加。该平台的发展本质是将通用PC硬件定位为专门的功能,如登录、计算、Web服务器、文件服务器和可视化引擎。这是对传统Beowulf集群的标准登录/计算二分法的逻辑扩展。显然,这些专门的节点(因此称为“集群设备”)共享大量的公共配置和软件。许多集群工具包缺乏的是跨设备和特定硬件共享配置的能力(应该共享的地方),并且只在需要的地方进行区分。在NPACI Rocks集群发行版中,我们开发了一个具有定义良好的继承属性的配置基础设施,它利用并构建了事实上的标准,包括:XML(带有标准解析器)、RedHat Kickstart、HTTP传输、CGI、SQL数据库和图形结构,以便轻松定义集群设备。我们的方法既不需要复制配置文件,也不需要构建“黄金”映像参考。通过依赖这种描述性和可编程的基础设施,并仔细地从软件包中划分配置信息(这是一种位传递机制),我们可以轻松地处理设备的异构性,轻松处理设备特定实例之间的小硬件差异(例如IDE与SCSI),并使用相同的基础设施支持大硬件差异(例如/spl times/86与IA64)。我们的机制很容易扩展到其他描述性基础设施(例如Solaris Jumpstart作为后端目标),并且已经在100多个集群上得到了验证(这些集群之间存在显著的硬件和配置差异)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Leveraging standard core technologies to programmatically build Linux cluster appliances
Clusters have made the jump from lab prototypes to full-fledged production computing platforms. The number variety, and specialized configurations of these machines are increasing dramatically with 32-128 node clusters being commonplace in science labs. The evolving nature of the platform is to target generic PC hardware to specialized functions such as login, compute, Web server file server and a visualization engine. This is the logical extension to the standard login/compute dichotomy of traditional Beowulf clusters. Clearly, these specialized nodes (henceforth "cluster appliances") share an immense amount of common configuration and software. What is lacking in many clustering toolkits is the ability to share configuration across appliances and specific hardware (where it should be shared) and differentiate only where needed In the NPACI Rocks cluster distribution, we have developed a configuration infrastructure with well-defined inheritance properties that leverages and builds on de facto standards including: XML (with standard parsers), RedHat Kickstart, HTTP transport, CGI, SQL databases, and graph constructs to easily define cluster appliances. Our approach neither resorts to replication of configuration files nor does it require building a "golden" image reference. By relying on this descriptive and programmatic infrastructure and carefully demarking configuration information from the software packages (which is a bit delivery mechanism), we can easily handle the heterogeneity of appliances, easily deal with small hardware differences among particular instances of appliances (such as IDE vs. SCSI), and support large hardware differences (like /spl times/86 vs. IA64) with the same infrastructure. Our mechanism is easily extended to other descriptive infrastructures (such as Solaris Jumpstart as a backend target) and has been proven on over a 100 clusters (with significant hardware and configuration differences among these clusters).
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