Heterogeneous Grid Environment Research Articles

Parallel programming on a high‐performance application‐runtime

AbstractHigh‐performance application development remains challenging, particularly for scientists making the transition to a heterogeneous grid environment. In general areas of computing, virtual environments such as Java and .Net have proved to be successful in fostering application development, allowing users to target and compile to a single environment, rather than a range of platforms, instruction sets and libraries. However, existing runtime environments are focused on business and desktop computing and they do not support the necessary high‐performance computing (HPC) abstractions required by e‐Scientists. Our work is focused on developing an application‐runtime that can support these services natively. The result is a new approach to the development of an application‐runtime for HPC: the Motor system has been developed by integrating a high‐performance communication library directly within a virtual machine. The Motor message passing library is integrated alongside and in cooperation with other runtime libraries and services while retaining a strong message passing performance. As a result, the application developer is provided with a common environment for HPC application development. This environment supports both procedural languages, such as C, and modern object‐oriented languages, such as C#. This paper describes the unique Motor architecture, presents its implementation and demonstrates its performance and use. Copyright © 2008 John Wiley & Sons, Ltd.

On the Design of Adaptive and Decentralized Load Balancing Algorithms with Load Estimation for Computational Grid Environments

In this paper, we address several issues that are imperative to grid environments such as handling resource heterogeneity and sharing, communication latency, job migration from one site to other, and load balancing. We address these issues by proposing two job migration algorithms, which are MELISA (modified ELISA) and LBA (load balancing on arrival). The algorithms differ in the way load balancing is carried out and is shown to be efficient in minimizing the response time on large and small-scale heterogeneous grid environments, respectively. MELISA, which is applicable to large-scale systems (that is, interGrid), is a modified version of ELISA in which we consider the job migration cost, resource heterogeneity, and network heterogeneity when load balancing is considered. The LBA algorithm, which is applicable to small-scale systems (that is, intraGrid), performs load balancing by estimating the expected finish time of a job on buddy processors on each job arrival. Both algorithms estimate system parameters such as the job arrival rate, CPU processing rate, and load on the processor and balance the load by migrating jobs to buddy processors by taking into account the job transfer cost, resource heterogeneity, and network heterogeneity. We quantify the performance of our algorithms using several influencing parameters such as the job size, data transfer rate, status exchange period, and migration limit, and we discuss the implications of the performance and choice of our approaches.

Specification and Runtime Workflow Support in the ASKALON Grid Environment

We describe techniques to support the runtime execution of scientific workflows in the ASKALON Grid environment. We present a formal model and three middleware services that support in combination the effective execution in heterogeneous and dynamic Grid environments: performance prediction, scheduling, and enactment engine. We validate our techniques with concrete experimental results for two real-world applications executed in the Austrian Grid environment.

SOLVING NONLINEAR WAVE EQUATIONS IN THE GRID COMPUTING ENVIRONMENT: AN EXPERIMENTAL STUDY

In this paper we are interested in studying the development of parallel algorithms to solve nonlinear wave equations. Both synchronous and asynchronous algorithms contexts are considered. The solver is based on the multisplitting Newton method that provides a coarse-grained scheme. Experiments are carried out in both homogeneous and heterogeneous grid environments. According to the configuration environment, the behaviors of parallel synchronous and asynchronous algorithms are analyzed. Experiments allow us to draw some conclusions about the use of parallel iterative algorithms in grid computing environment.

Synchronous and asynchronous solution of a 3D transport model in a grid computing environment

Numerical simulation is a common approach to understand many phenomena, usually yielding a computationally intensive problem. To overcome insufficient computer capacity and computational speed, a grid computing environment is a suitable approach. In this paper we focus on the development of parallel algorithms to solve a 3D transport model in such a context. The solver is based on the multisplitting Newton method that provides a coarse-grained scheme. Algorithms are implemented using JACE, a grid-enabled Java Asynchronous Computing Environment. This programming environment allows users to design synchronous and asynchronous parallel iterative algorithms as well. Experiments are carried out on a heterogeneous grid environment in which the behaviour of both parallel iterative algorithms is analysed. The results allow us to draw some conclusions about the use of the programming library JACE and the design of parallel iterative algorithms in a grid computing environment.

GCM: a grid configuration manager for heterogeneous grid environments

Deploying grid technologies by distributing an application over several machines is widely emerging for large scientific simulations. While in the last couple of years distributed simulations were often executed on a pure demonstration level, currently ongoing work is focusing on taking the steps necessary to use the technology in an everyday production environment. This paper presents the Grid Configuration Manager (GCM), a tool developed to hide the complexity and ease the handling of scientific, computational jobs in heterogeneous grid environments, by abstracting the necessary tasks and implementing them for the most widespread grid middleware (Globus, UNICORE) and traditional access mechanism (SSH).