Summary form only given. Kernel coupling quantifies the interaction between adjacent and chains of kernels in an application. A kernel can be a loop, procedure or file. In our previous work, we used the kernel coupling values to identify how to combine the execution times of the individual kernels that compose the application to predict the execution time of the full application. The results of this previous work using the NAS Parallel Benchmark SP demonstrated that the use of coupling values resulted in very good predictions with average errors in the range of only 1.18% in contrast to simply summing the execution times of the kernels that resulted in average errors in the range of 20.54%. The major concern with the coupling values is the fact that values are needed for each different problem size, number of processors and machine. We explore the ability to reuse coupling values. In particular, we explore the reuse in terms of the three dimensional space consisting of the following axes: number of processors, problem size and system architecture. The experimental results indicate that when considering parallel systems, with increasing number of processors and problem sizes, we found clear transitions with the coupling values resulting in the ability to reuse values. Further, reusing coupling values is feasible on classes of systems such as clusters, distributed shared memory and other distributed memory systems.

Performance models provide significant insight into the performance relationships between an application and the system used for execution. The major obstacle to developing performance models is the lack of knowledge about the performance relationships between the different functions that compose an application. This paper addresses the issue by using a coupling parameter, which quantifies the interaction between kernels, to develop performance predictions. The results, using three NAS parallel application benchmarks, indicate that the predictions using the coupling parameter were greatly improved over a traditional technique of summing the execution times of the individual kernels in an application. In one case the coupling predictor had less than 1% relative error in contrast the summation methodology that had over 20% relative error. Further, as the problem size and number of processors scale, the coupling values go through a finite number of major value changes that is dependent on the memory subsystem of the processor architecture.

Efficient execution of applications requires insight into how the system features impact the performance of the application. For distributed systems, the task of gaining this insight is complicated by the complexity of the system features. This insight generally results from significant experimental analysis and possibly the development of performance models. This paper presents the Prophesy project, an infrastructure that aids in gaining this needed insight based upon experience. The core component of Prophesy is a relational database that allows for the recording of performance data, system features and application details.

High-speed wide-area networks are expected to enable innovative applications that integrate geographically distributed, high-performance computing, database, graphics and networking resources. However, there is as yet little understanding of the higher-level services required to support these applications, or of the techniques required to implement these services in a scalable, secure manner. We report on a large-scale prototyping effort that has yielded some insights into these issues. Building on the hardware base provided by the I-WAY, a national-scale asynchronous transfer mode (ATM) network, we developed an integrated management and application programming system, called I-Soft. This system was deployed at most of the 17 I-WAY sites and used by many of the 60 applications demonstrated on the I-WAY network. In this paper we describe the I-Soft design and report on lessons learned from application experiments. We focus on four novel concepts that we believe may have relevance to future, similar systems: point of presence machines as a means of simplifying implementation and management; scheduler proxies to integrate local schedulers to computational resource brokers; authentication proxies to provide a uniform authentication environment across multiple administrative domains; and network-aware parallel programming tools to hide heterogeneity and improve performance in heterogeneous environments. Lessons learned in building I-Soft have motivated subsequent research and development efforts in the Globus project. © 1998 John Wiley & Sons, Ltd.

High speed wide area networks are expected to enable innovative applications that integrate geographically distributed, high performance computing, database, graphics, and networking resources. However, there is as yet little understanding of the higher level services required to support these applications, or of the techniques required to implement these services in a scalable, secure manner. We report on a large scale prototyping effort that has yielded some insights into these issues. Building on the hardware base provided by the I-WAY, a national scale asynchronous transfer mode (ATM) network, we developed an integrated management and application programming system, called I-Soft. This system was deployed at most of the 17 I-WAY sites and used by many of the 60 applications demonstrated on the I-WAY network. We describe the I-Soft design and report on lessons learned from application experiments.

Metacomputing systems use high-speed networks to connect supercomputers, mass storage systems, scientific instruments, and display devices with the objective of enabling parallel applications to utilize geographically distributed computing resources. However, experience shows that high performance can often be achieved only if applications can integrate diverse communication substrates, transport mechanisms, and protocols, chosen according to where communication is directed, what is communicated, or when communication is performed. In this paper, we describe a software architecture that addresses this requirement. This architecture allows multiple communication methods to be supported transparently in a single application, with either automatic or user-specified selection criteria guiding the methods used for each communication. We describe an implementation of this architecture, based on the Nexus communication library, and use this implementation to evaluate performance issues. This implementation was used to support a wide variety of applications in the I-WAY metacomputing experiment at Supercomputing~95; we use one of these applications to provide a quantitative demonstration of the advantages of multimethod communication in a heterogeneous networked environment.