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.

Applications designed to execute on "computational grids" frequently require the simultaneous co-allocation of multiple resources in order to meet performance requirements. For example, several computers and network elements may be required in order to achieve real-time reconstruction of experimental data, while a large numerical simulation may require simultaneous access to multiple supercomputers. Motivated by these concerns, we have developed a general resource management architecture for Grid environments, in which resource co-allocation is an integral component. In this paper, we examine the coallocation problem in detail and present mechanisms that allow an application to guide resource selection during the co-allocation process; these mechanisms address issues relating to the allocation, monitoring, control, and configuration of distributed computations. We describe the implementation of co-allocators based on these mechanisms and present the results of microbenchmark studies and largescale application experiments that provide insights into the costs and practical utility of our techniques.

Improvements in the performance of processors and networks make it both feasible and interesting to treat collections of workstations, servers, clusters, and supercomputers as integrated computational resources, or Grids. However, the highly heterogeneous and dynamic nature of such Grids can make application development dicult. Here we describe an architecture and prototype implementation for a Grid-enabled computational framework based on Cactus, the MPICH-G2 Grid-enabled message-passing library, and a variety of specialized features to support efficient execution in Grid environments. We have used this framework to perform record-setting computations in numerical relativity, running across four supercomputers and achieving scaling of 88% (1140 CPU's) and 63% (1500 CPUs). The problem size we were able to compute was about five times larger than any other previous run. Further, we introduce and demonstrate adaptive methods that automatically adjust computational parameters during run time, to increase dramatically the efficiency of a distributed Grid simulation, without modification of the application and without any knowledge of the underlying network connecting the distributed computers.

Improvements in the performance of processors and networks means that it can be both feasible and interesting to treat collections of workstations, servers, clusters, and supercomputers as integrated computational resources or Grids. However, the highly heterogeneous and dynamic nature of such Grids makes application development extremely difficult. Here we describe an architecture and prototype implementation for a Grid-enabled computational framework called Cactus-G. This framework integrates the Cactus simulation system with the MPICH-G2 Grid-enabled message passing library and in addition integrates a variety of specialized features to support efficient execution in Grid environments.

Abstract—This paper presents a programmable multi-granular optical cross connect (MG-OXC) and network architecture deployable in multi-service and multi-provider networks. The concept of programmable MG-OXC is introduced to provide a way of utilizing multiple switching/transport granularities to efficiently support the emerging traffic demands in both core and metro networks. For this reason, the supported bandwidth granularities include full lambdas, sub- and super-lambdas and multiple transport formats such as bursts, flows and packets. The programmability is envisaged by a software/hardware platform that simplifies network control, re-planning at the logical level and end-to-end service transparency, by translating the technology-specific information to technology independent services in an abstracted and logical manner. Keywords-component; multi-granular optical cross connects, programmable networks, optical burst switching I.