Abstract Many production Grid and e‐Science infrastructures have begun to offer services to end‐users during the past several years with an increasing number of scientific applications that require access to a wide variety of resources and services in multiple Grids. Therefore, the Grid Interoperation Now—Community Group of the Open Grid Forum—organizes and manages interoperation efforts among those production Grid infrastructures to reach the goal of a world‐wide Grid vision on a technical level in the near future. This contribution highlights fundamental approaches of the group and discusses open standards in the context of production e‐Science infrastructures. Copyright © 2009 John Wiley & Sons, Ltd.

In this paper we present 411, a password distribution system for high performance environments that provides security and scalability. We show that existing solutions such as NIS and Kerberos do not provide sufficient performance in large, tightly coupled systems such as computational clusters. Unlike existing single-signon services, the 411 design removes the need for communication during password lookup by using aggressive replication techniques. We demonstrate the use of shared keys to efficiently protect user information, and the careful management of system wide consistency and fault tolerance. A theoretical analysis of the behavior of 411 is matched with quantitative evidence of its performance and suitability to a clustered environment. We further show the system effectively responds to stress by simulating 50% message loss on a 60-node cluster. This protocol is currently used worldwide in hundreds of Rocks-based production systems to provide password and login information service.

The Rocks toolkit uses a graph-based framework to describe the configuration of all node types (termed appliances) that make up a complete cluster. With hundreds of deployed clusters, our turnkey systems approach has shown to be quite easily adapted to different hardware and logical node configurations. However, the Rocks architecture and implementation contains a significant asymmetry: the graph definition of all appliance types except the initial frontend can be modified and extended by the end-user before installation. However, frontends can be modified only afterward by hands-on system administration. To address this administrative discontinuity between nodes and frontends, we describe the design and implementation of Rolls. First and foremost, Rolls provide both the architecture and mechanisms that enable the end-user to incrementally and programmatically modify the graph description for all appliance types. New functionality can be added and any Rocks-supplied software component can be overwritten or removed simply by inserting the desired Roll CD(s) at installation time. This symmetric approach to cluster construction has allowed us to shrink the core of the Rocks implementation while increasing flexibility for the end-user. Rolls are optional, automatically configured, cluster-aware software systems. Current add-ons include: scheduling systems (SGE, PBS), grid support (based on NSF Middleware Initiative), database support (DB2), Condor, integrity checking (Tripwire) and the Intel compiler. Community-specific Rolls can be and are developed by groups outside of the Rocks core development group.

In this paper, we present a structure for monitoring a large set of computational clusters. We illustrate methods for scaling a monitor network comprised of many clusters while keeping processing requirements low. A design for presenting high-level Web-based summaries of the monitor network is provided, along with a generalization to a distributed, multiple-resolution monitoring tree. Emphasis is placed on scalability, fast query response, fault tolerance, and grid compatibility. Experimental evidence is presented that demonstrates the performance of our design.

Abstract High‐performance computing clusters (commodity hardware with low‐latency, high‐bandwidth interconnects) based on Linux are rapidly becoming the dominant computing platform for a wide range of scientific disciplines. Yet, straightforward software installation, maintenance, and health monitoring for large‐scale clusters has been a consistent and nagging problem for non‐cluster experts. The NPACI Rocks distribution takes a fresh perspective on management and installation of clusters to dramatically simplify software version tracking and cluster integration. NPACI Rocks incorporates the latest Red Hat distribution (including security patches) with additional cluster‐specific software. Using the identical software tools used to create the base distribution, users can customize and localize Rocks for their site. Strong adherence to widely‐used (de facto) tools allows Rocks to move with the rapid pace of Linux development. Version 2.2.1 of the toolkit is available for download and installation. Over 100 Rocks clusters have been built by non‐cluster experts at multiple institutions (residing in various countries) providing a peak aggregate of 2 TFLOPS of clustered computing. Copyright © 2003 John Wiley & Sons, Ltd.

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).

High-performance computing clusters (commodity hardware with low-latency, high-bandwidth interconnects) based on Linux, are rapidly becoming the dominant computing platform for a wide range of scientific disciplines. Yet, straightforward software installation, maintenance, and health monitoring for large-scale clusters has been a consistent and nagging problem for non-cluster experts. The NPACI Rocks toolkit takes a fresh perspective on management and installation of clusters to dramatically simplify software version tracking, and cluster integration. The toolkit incorporates the latest Red Hat distribution (including security patches) with additional cluster-specific software. Using the identical software tools used to create the base distribution, users can customize and localize Rocks for their site. Strong adherence to widely-used (de facto) tools allows Rocks to move with the rapid pace of Linux development. Version 2.1 of the toolkit is available for download and installation. To date, 10 clusters spread among 5 institutions have been built using this toolkit.