Advances in networking technologies will soon make it possible to use the global information infrastructure in a qualitatively different way—as a computational resource as well as an information resource. This idea for an integrated computation and information resource called the Computational Power Grid has been described by the recent book entitled The Grid: Blueprint for a New Computing Infrastructure [18]. The Grid will connect the nation’s computers, databases, instruments, and people in a seamless web, supporting emerging computation-rich application concepts such as remote computing, distributed supercomputing, tele-immersion, smart instruments, and data mining. To realize this vision, significant scientific and technical obstacles must be overcome. Principal among these is usability. Because the Grid will be inherently more complex than existing computer systems, programs that execute on the Grid will reflect some of this complexity. Hence, making Grid resources useful and accessible to scientists and engineers will require new software tools that embody major advances in both the theory and practice of building Grid applications. The goal of the Grid Application Development Software (GrADS) Project is to simplify distributed heterogeneous computing in the same way that the World Wide Web simplified information sharing

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ASSIST (A Software development System based upon Integrated Skeleton Technology) is a programming environment oriented to the development of parallel and distributed high-performance applications according to a unified approach. The language and implementation features of ASSIST are a result of our long-term research in parallel programming models and tools. ASSIST is evolving towards programming environments for high-performance complex enabling platforms, especially Grids. In this paper, we show how ASSIST can act as a valid research vehicle to study, experiment and realize Grid-aware programming environments for high-performance applications. Special emphasis is put on the innovative methodologies, strategies and tools for dynamically adaptive applications, that represent the necessary step for the success of Grid platforms. First we discuss the conceptual framework for Grid-aware programming environments, based upon structured parallel programming and components technology, anticipating how ASSIST possesses the essential features required by

This paper describes an overall framework for the design of numerical libraries on a computational Grid of processors where the processors may be geographically distributed and under the control of a Grid-based scheduling system. A set of experiments are presented in the context of solving systems of linear equations using routines from the ScaLAPACK software collection along with various grid service components, such as Globus, NWS, and Autopilot. Motivation On The Grid The goal of the Grid Application Development Software (GrADS) project [1] is to simplify distributed heterogeneous computing in the same way that the World Wide Web simplified information sharing over the Internet. The GrADS project is exploring the scientific and technical problems that must be solved to make Grid applications development and performance tuning for real applications an everyday practice. This requires research in four key areas; each validated in a prototype infrastructure that will make programming on grids a routine task: 1. Grid software architectures that facilitate information flow and resource negotiation among applications, libraries, compilers, linkers, and runtime systems; 2. Base software technologies, such as scheduling, resource discovery, and communication, to support development and execution of performance-efficient Grid applications; 3. Languages, compilers, environments, and tools to support creation of applications for the Grid and solution of problems on the Grid; and 4. Mathematical and data structure libraries for Grid applications, including numerical methods for control of accuracy and latency tolerance.

Data Grids have been adopted as the platform for scientific communities that need to share, access, transport, process and manage large data collections distributed worldwide. They combine high-end computing technologies with high-performance networking and wide-area storage management techniques. In this paper, we discuss the key concepts behind Data Grids and compare them with other data sharing and distribution paradigms such as content delivery networks, peer-to-peer networks and distributed databases.

Applications on a Computational Grid must meet stringent performance requirements even when the performance characteristics of the underlying systems and networks vary significantly at runtime. Runtime adaptation can be used to tolerate such changes, but adaptive codes can be challenging to design and debug. This papers propose a language called Program Control Language (PCL) that provides a novel means of specifying adaptations in distributed applications. PCL is based on an abstract, global representation of the distributed program that enables one to reason about and describe application-specific adaptation strategies at a high level, using a few key mechanisms. The global representation enables distributed performance metrics and adaptations to be specified in simple, global terms and implemented transparently by the compiler and runtime system. The paper describes the conceptual adaptation framework, the PCL language, and our implementation of the PCL compiler and runtime system. The paper uses two examples to illustrate the capabilities and benefits of PCL, and to show experimentally that the performance overheads of using PCL for implementing an adaptive application are negligible.

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Understanding the dynamic behavior of parallel programs is key to developing efficient system software and runtime environments; this is even more true on emerging computational Grids where resource availability and performance can change in unpredictable ways. Event tracing provides details on behavioral dynamics, albeit often at great cost. We describe an intermediate approach, based on curve fitting, that retains many of the advantages of event tracing but with lower overhead. These compact "application signatures" summarize the time-varying resource needs of scientific codes from historical trace data.

Developing grid applications is a challenging endeavor, which at the moment requires both extensive labor and expertise. The Grid Application Development Software Project (GRADS) provides a system to simplify grid application development. This system incorporates tools at all stages of the application development and execution cycle. In this chapter we focus on application scheduling, and present the three scheduling approaches developed in GRADS: development of an initial application schedule (launch-time scheduling), modification of the execution platform during execution (rescheduling), and negotiation between multiple applications in the system (metascheduling). These approaches have been developed and evaluated for platforms that consist of distributed networks of shared workstations, and applied to real-world parallel applications.

Grids are semantically different from other distributed systems. Therefore, performance analysis, just like any other technique requires careful reconsideration. This paper analyses the fundamental differences between grids and other systems and points out the special requirements raised to performance analysis. The aim of this paper is to survey the special problems, the possible directions and the existing solutions. A monitoring system, that is able to support the posed requirements is introduced as an example.