Although molecular dynamics (MD) simulations of biomolecular systems often run for days to months, many events of great scientific interest and pharmaceutical relevance occur on long time scales that remain beyond reach. We present several new algorithms and implementation techniques that significantly accelerate parallel MD simulations compared with current state-of-the-art codes. These include a novel parallel decomposition method and message-passing techniques that reduce communication requirements, as well as novel communication primitives that further reduce communication time. We have also developed numerical techniques that maintain high accuracy while using single precision computation in order to exploit processor-level vector instructions. These methods are embodied in a newly developed MD code called Desmond that achieves unprecedented simulation throughput and parallel scalability on commodity clusters. Our results suggest that Desmond's parallel performance substantially surpasses that of any previously described code. For example, on a standard benchmark, Desmond's performance on a conventional Opteron cluster with 2K processors slightly exceeded the reported performance of IBM's Blue Gene/L machine with 32K processors running its Blue Matter MD code.

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.

Wide-area grid deployments are becoming a standard for shared cyberinfrastructure within scientific domain communities. These systems enable resource sharing, data management and publication, collaboration, and shared development of community resources. This work describes the systems management solution developed for one such grid deployment, the GEON Grid (GEOsciences Network), a domain-specific grid of clusters for geological research. GEON provides a standardized base software stack across all sites to ensure interoperability while providing structures that allow local customization. This situation gives rise to a set of requirements that are difficult to satisfy with existing tools. Cluster management software is available that allows administrators to specify and install a common software stack on all nodes of a single cluster and enable centralized control and diagnostics of its components with minimal effort. While grid deployments have similar management requirements to computational clusters, they have faced a lack of available tools to address their needs. We describe extensions to the Rocks cluster distribution to satisfy several key goals of the GEON Grid, and show how these wide-area cluster integration extensions satisfy the most important of these goals.

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.