The Globus project is a multi-institutional research e#ort that seeks to enable the construction of computational grids providing pervasive, dependable, and consistent access to high-performance computational resources, despite geographical distribution of both resources and users. Computational grid technology is being viewed as a critical element of future highperformance computing environments that will enable entirely new classes of computation-oriented applications, much as the World Wide Web fostered the development of new classes of information-oriented applications. In this paper, we report on the status of the Globus project as of early 1998. We describe the progress that has been achieved to date in the development of the Globus toolkit, a set of core services for constructing grid tools and applications. We also discuss on the Globus Ubiquitous Supercomputing Testbed (GUSTO) that we have constructed to enable largescale evaluation of Globus technologies, and review early exp...

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Writing parallel applications for computational grids is a challenging task. To achieve good performance, algorithms designed for local area networks must be adapted to the differences in link speeds. An important class of algorithms are collective operations, such as broadcast and reduce. We have developed MAGPIE, a library of collective communication operations optimized for wide area systems. MAGPIE's algorithms send the minimal amount of data over the slow wide area links, and only incur a single wide area latency. Using our system, existing MPI applications can be run unmodified on geographically distributed systems. On moderate cluster sizes, using a wide area latency of 10 milliseconds and a bandwidth of 1 MByte/s, MAGPIE executes operations up to 10 times faster than MPICH, a widely used MPI implementation; application kernels improve by up to a factor of 4. Due to the structure of our algorithms, MAGPIE's advantage increases for higher wide area latencies.

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.

The ecient implementation of collective communication operations has received much attention. Initial eorts modeled network communication and produced \optimal" trees based on those models. However, the models used by these initial eorts assumed equal point-to-point latencies between any two processes. This assumption is violated in heterogeneous systems such as clusters of SMPs and wide-area \computational grids", and as a result, collective operations that utilize the trees generated by these models perform suboptimally. In response, more recent work has focused on creating topology-aware trees for collective operations that minimize communication across slower channels (e.g., a wide-area network). While these efforts have signicant communication benets, they all limit their view of the network to only two layers. We present a strategy based upon a multilayer view of the network. By creating multilevel topology trees we take advantage of communication cost dierences at every lev...

In computational grids, performance-hungry applications need to simultaneously tap the computational power of multiple, dynamically available sites. The crux of designing grid programming environments stems exactly from the dynamic availability of compute cycles: grid programming environments (a) need to be portable to run on as many sites as possible, (b) they need to be flexible to cope with different network protocols and dynamically changing groups of compute nodes, while (c) they need to provide efficient (local) communication that enables high-performance computing in the first place. Existing programming environments are either portable (Java), or they are flexible (Jini, Java RMI), or they are highly efficient (MPI). No system combines all three properties that are necessary for grid computing. In this paper, we present Ibis, a new programming environment that combines Java’s “run everywhere ” portability both with flexible treatment of dynamically available networks and processor pools, and with highly efficient, object-based communication. Ibis can transfer Java objects very efficiently by combining streaming object serialization with a zero-copy protocol. Using RMI as a simple test case, we show that Ibis outperforms existing RMI implementations, achieving up to 9 times higher throughputs with trees of objects. 1

... In this paper, we explain why CoG Kits are important, describe the design and implementation of a Java CoG Kit, and use examples to illustrate how CoG Kits can enable new approaches to application development based on the integrated use of commodity and Grid technologies.

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In this paper we propose an adaptive scheduling approach designed to improve the performance of parallel applications in Computational Grid environments. A primary contribution of our work is that our design is modular and provides a separation of the scheduler itself from the application-specific components needed for the scheduling process. As part of the scheduler, we have also developed a search procedure which effectively and efficiently identifies desirable schedules. As test cases for our approach, we selected two applications from the class of iterative, mesh-based applications. For each of the test applications, we developed data mappers and performance models. We used a prototype of our approach in conjunction with these application-specific components to perform validation experiments in production Grid environments. Our results show that our scheduler provides significantly better application performance than conventional scheduling strategies. We also show that our scheduler gracefully handles degraded levels of availability of application and Grid resource information. Finally, we demonstrate that the overheads introduced by our methodology

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 widearea Java system, called Manta. Manta implements the Java 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 Myrinet-based clusters connected by ATM WANs. 1 Introduction Metacomputing is an interesting research area that tries to integrate geographically distributed computing resources into a single powerful system. Many applications can benefit from such an integration [11, 22]. Metacomputing systems support such...