Abstract not found

Application development for high-performance distributed computing systems, or computational grids as they are sometimes called, requires "grid-enabled" tools that hide mundane aspects of the heterogeneous grid environment without compromising performance. As part of an investigation of these issues, we have developed MPICH-G, a grid-enabled implementation of the Message Passing Interface (MPI) that allows a user to run MPI programs across multiple computers at different sites using the same commands that would be usedonaparallel computer. This library extends the Argonne MPICH implementation of MPI to use services provided by the Globus grid toolkit. In this paper, we describe the MPICH-G implementation and present preliminary performance results.

Application development for distributed-computing ‘‘Grids’ ’ can benefit from tools that variously hide or enable application-level management of critical aspects of the heterogeneous environment. As part of an investigation of these issues, we have developed MPICH-G2, a Grid-enabled implementation of the Message Passing Interface (MPI) that allows a user to run MPI programs across multiple computers, at the same or different sites, using the same commands that would be used on a parallel computer. This library extends the Argonne MPICH implementation of MPI to use services provided by the Globus Toolkit for authentication, authorization, resource allocation, executable staging, and I/O, as well as for process creation, monitoring, and control. Various performance-critical operations, including startup and collective operations, are configured to exploit network topology information. The library also exploits MPI constructs for performance management; for example, the MPI communicator construct is used for application-level discovery of, and adaptation to, both network topology and network quality-of-service mechanisms. We describe the MPICH-G2 design and implementation, present performance results, and review application experiences, including record-setting distributed simulations.

Loop distribution is one of the most useful techniques to reduce the execution time of parallel applications. Traditionally, loop scheduling algorithms are implemented based on parallel programming paradigms such as MPI. This approximation presents three main disadvantages when applied in a Grid environment, namely: (i) all resources must be simultaneously allocated to begin execution of the application; (ii) it is necessary to restart the whole application when a resource fails; (iii) it is not possible to add new resources to a currently running application. To overcome these limitations, we propose a new approach to implement loop distribution schemes in computational Grids. This approach is implemented using the Distributed Resource Management Application API (DRMAA) standard and the GridWay meta-scheduling framework. The efficiency of this approach to solve the Mandelbrot set problem is analyzed in a Globus-based research testbed. 1