Program development environments are instrumental in providing users with easy and efficient access to parallel computing platforms. While a number of such environments have been widely accepted and used for traditional HPC systems, there are currently no widely used environments for Grid programming. The goal of the Grid Application Development Software (GrADS) project is to develop a coordinated set of tools, libraries and run-time execution facilities for Grid program development. In this paper, we describe a Grid scheduler component that is integrated as part of the GrADS software system. Traditionally, application-level schedulers (e.g. AppLeS) have been tightly integrated with the application itself and were not easily applied to other applications. Our design is generic: we decouple the scheduler core (the search procedure) from the application-specific (e.g. application performance models) and platformspecific (e.g. collection of resource information) components used by the search procedure. We provide experimental validation of our approach for two representative regular, iterative parallel programs in a variety of real-world Grid testbeds. Our scheduler consistently outperforms static and user-driven scheduling methods. This material is based upon work supported by the National Science Foundation under Grant #9975020.

Abstract not found

Java’s support for parallel and distributed processing makes the language attractive for metacomputing applications, such as parallel applications that run on geographically distributed (wide-area) systems. To obtain actual experience with a Java-centric approach to metacomputing, we have built and used a high-performance wide-area Java system, called Manta. Manta implements the Java Remote Method Invocation (RMI) model using different communication protocols (active messages and TCP/IP) for different networks. The paper shows how widearea parallel applications can be expressed and optimized using Java RMI. Also, it presents performance results of several applications on a wide-area system consisting of four Myrinetbased clusters connected by ATM WANs. We finally discuss alternative programming models, namely object replication, JavaSpaces, and MPI for Java.

This paper describes an experiment in which a largescale scientific application developed for tightly-coupled parallel machines is adapted to the distributed execution environment of the Information Power Grid (IPG). A brief overview of the IPG and a description of the computational fluid dynamics (CFD) algorithm are given. The Globus metacomputing toolkit is used as the enabling device for the geographically-distributed computation. Modifications related to latency hiding and load balancing were required for an efficient implementation of the CFD application in the IPG environment. Performance results on a pair of SGI Origin2000 machines indicate that real scientific applications can be effectively implemented on the IPG; however, a significant amount of continued effort is required to make such an environment useful and accessible to scientists and engineers. 1.

The emergence of meta computers and computational grids makes it feasible to run parallel programs on large-scale, geographically distributed computer systems. Writing parallel applications for such systems is a challenging task which may require changes to the communication structure of the applications. MPI's collective operations (such as broadcast and reduce) allow for some of these changes to be hidden from the applications programmer. We have developed MAGPIE, a library of collective communication operations optimized for wide area systems. MAGPIE 's algorithms are designed to send the minimal amount of data over the slow wide area links, and to only incur a single wide area latency. This paper discusses MPI's collective reduction operations. Compared to systems that do not take the topology into account, such as MPICH, large performance improvements are possible. For larger messages, best performance is achieved when the reduction function is associative. 1 Introduction Severa...

Distributed systems, which consist of a collection of high performance systems interconnected via high performance networks (e.g. ATM), are becoming feasible platforms for execution of large-scale, complex problems. In this paper, we address various issues related to mesh partitioning for distributed systems. These issues include the metric used to compare different partitions, efficiency of the application executing on a distributed system, the number of cut sets, and the advantage of exploiting heterogeneity in network performance. We present a tool called PART, for automatic mesh partitioning for distributed systems. The novel feature of PART is that it considers heterogeneities in the application and the distributed system. The heterogeneities in the distributed system include processor and network performance; the heterogeneities in the application include computational complexities. Preliminary results are presented for partitioning regular and irregular finite element meshes for...

This paper describes work in progress to develop a component-based software infrastructure, called Padico, for computational grids based on the CORBA Component Model from the OMG. The objective of Padico is to offer a component model targeting multi-physics simulations or any applications that require the coupling of several codes (simulation or visualization) within a high-performance environment. This paper addresses mainly two issues we i-dentified as important for a grid-aware component model. The first issue deals with the encapsulation of parallel codes into components. We propose an extension to the CORBA component model called GridCCM. The second issue addresses the problem of the communication between components within a computational grid. We propose a portable runtime, called PadicoTM, able to efficiently support communication in a heterogeneous networking environment. 1

In this paper we study the problem of redistributing in parallel data between clusters interconnected by a backbone. This problem is a generalization of the well-known redistribution problem that appears in parallelism [9]. We suppose that at most k communications can be performed atthe same time (the value of

We discuss algorithms and tools to help program and use metacomputing resources in the forthcoming years. Metacomputing with highly distributed heterogeneous environments stands to become a major, if not dominant, method to implement all kinds of parallel applications. In this report, we survey some general aspects of metacomputing (hardware, system and administration issues, as well as the application eld). Next we identify some algorithmic issues and software challenges that must be solved to eÆciently program and/or transparently use such platforms: Data decomposition techniques for cluster computing, Granularity issues for metacomputing, Scheduling and load-balancing methods, Programming models. We illustrate each of these issues and challenges by the analysis of several case studies: Cluster ScaLAPACK, AppLeS, Globus, Legion, Albatross and Netsolve. We conclude this report by stating some nal remarks and recommendations. mbox Acknowledgments: This research report is...

In this paper, we present ParaPART, a parallel version of a mesh partitioning tool, called PART, for distributed systems. PART takes into consideration the heterogeneities in processor performance, network performance and application computational complexities to achieve a balanced estimate of execution time across the processors in the distributed system. Simulated annealing is used in PART to perform the backtracking search for desired partitions. ParaPART significantly improves performance of PART by using the asynchronous multiple Markov chain approach of parallel simulated annealing. ParaPART is used to partition six irregular meshes into 8, 16, and 100 subdomains using up to 64 client processors on an IBM SP2 machine. The results show superlinear speedup in most cases and nearly perfect speedup for the rest. Using the partitions from ParaPART, we ran an explicit, 2-D finite element code on two geographically distributed IBM SP machines. Results indicate that ParaPART produces r...