High-performance execution in distributed computing environments often requires careful selection and configuration not only of computers, networks, and other resources but also of the protocols and algorithms used by applications. Selection and configuration in turn require access to accurate, up-to-date information on the structure and state of available resources. Unfortunately no standard mechanism exists for organizing or accessing such information. Consequently different tools and applications adopt ad hoc mechanisms, or they compromise their portability and performance by using default configurations. We propose a Metacomputing Directory Service that provides efficient and scalable access to diverse, dynamic, and distributed information about resource structure and state. We define an extensible data model to represent required information and present a scalable, high-performance, distributed implementation. The data representation and application programming interface are adopted from the Lightweight Directory Access Protocol; the data model and implementation are new. We use the Globus distributed computing toolkit to illustrate how this directory service enables the development of more flexible and efficient distributed computing services and applications.

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A directory service for configuring high-performance distributed computations

The coming of giga-bit networks makes possible the realization of a single nationwide virtual computer comprised of a variety of geographically distributed high-performance machines and workstations. T o realize the potential that the physical infrastructure provides, software must be developed that is easy to use, supports lar ge degrees of parallelism in applications code, and manages the complexity of the underlying physical system for the user . This paper describes our approach to constructing and exploiting such “metasystems”. Our approach inherits features of earlier work on parallel processing systems and heterogeneous distributed computing systems. In particular , we are building on Mentat, an object-oriented parallel processing system developed at the University of V irginia. This report is a preliminary document. W e expect changes to occur as the architecture and design of the system mature.

Legion: The Next Logical Step Toward a Nationwide Virtual Computer

The sections in this article are


1
Examples of HC Application Studies

2
Examples of HC Environments and Tools

3
PVM and HeNCE

4
Taxonomies of Heterogeneous Computing

5
A Conceptual Model of Heterogeneous Computing

6
Task Profiling and Analytical Benchmarking

7
Matching and Scheduling

8
Matching and Scheduling Metatasks

9
Summary and Future Directions

10
Acknowledgment

Heterogeneous Distributed Computing

Mentat is an object-oriented parallel processing system designed to simplify the task of writing portable parallel programs for parallel machines and workstation networks. The Mentat compiler and run-time system work together to automatically manage the communication and synchronization between objects. The run-time system marshals member function arguments, schedules objects on processors, and dynamically constructs and executes large-grain data dependence graphs. In this article we present the Mentat run-time system. We focus on three aspects—the software architecture, including the interface to the compiler and the structure and interaction of the principle components of the run-time system; the run-time overhead on a component-by-component basis for two platforms, a Sun SparcStation 2 and an Intel Paragon; and an analysis of the minimum granularity required for application programs to overcome the run-time overhead.

https://www.cs.virginia.edu/~grimshaw/publications/p139-grimshaw.pdf

Portable run-time support for dynamic object-oriented parallel processing

There has been a recent increase of interest in heterogeneous computing systems, due partly to the fact that a single parallel architecture may not be adequate for exploiting all of a program's available parallelism. In some cases, heterogeneous systems have been shown to produce higher performance for lower cost than a single large machine. However, there has been only limited work on developing techniques and frameworks for partitioning and scheduling applications across the components of a heterogeneous system. In this paper we propose a general model for describing and evaluating heterogeneous systems that considers the degree of uniformity in the processing elements and the communication channels as a measure of the heterogeneity in the system. We also propose a class of dynamic scheduling algorithms for a heterogeneous computing system interconnected with an arbitrary communication network. These algorithms execute a novel optimization technique to dynamically compute schedules based on the potentially non-uniform computation and communication costs on the processors of a heterogeneous system. A unique aspect of these algorithms is that they easily adapt to different task granularities, to dynamically varying processor and system loads, and to systems with varying degrees of heterogeneity. Our simulations are designed to facilitate the evaluation of different scheduling algorithms under varying degrees of heterogeneity. The results show improved performance for our algorithms compared to the performance resulting from existing scheduling techniques.

Dynamic scheduling techniques for heterogeneous computing systems

Large meta-systems comprised of a variety of interconnected high-performance architectures are becoming available to researchers. To fully exploit these new systems software support must be provided that is easy to use, supports large degrees of parallelism in applications code, and manages the complexity of the underlying physical architecture for the user, This paper describes our approach to constructing and exploiting meta-systems. Our approach inherits features of earlier work on parallel processing systems and heterogeneous distributed computing systems. In particular, we build on Mentat, an object-oriented parallel processing system developed at the University of Virginia that provides large amounts of easy-to-use parallelism for MIMD architectures.'

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A.S. Grimshaw

Papers

Meta-Systems: An Approach Combining Parallel Processing and Heterogeneous Distributed Computing Systems