YellowRiver: A Flexible High Performance Cluster Computing Service for Grid

  • Authors:
  • Liang Peng;Lip Kian Ng;Simon See

  • Affiliations:
  • Asia Pacific, Sun Microsystems Inc., Nanyang Technological University;Asia Pacific, Sun Microsystems Inc., Nanyang Technological University;Asia Pacific, Sun Microsystems Inc., Nanyang Technological University

  • Venue:
  • HPCASIA '05 Proceedings of the Eighth International Conference on High-Performance Computing in Asia-Pacific Region
  • Year:
  • 2005

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Abstract

Computational Grids provide an emerging highly distributed computing platform for scientific computing. Recently, service oriented architecture (SOA) has become a trend of implementing software systems including Grids. SOA provides more flexibilities for Grid users at the service level. High performance computing (HPC) facilities such as HPC clusters, as building blocks of Grid computing, are playing an important role in computational Grid and they are embracing SOA when integrated into Grid in the format of services. Currently, how to build flexible and easy-to-use HPC service for Grid computing still remains an open topic and not much work has been done in this area. In this paper, we propose an HPC cluster service architecture for Grid computing and utility computing. It provides the basic function such as service deployment, service monitoring, and service execution, etc. HPC cluster service deployment not only includes normal application deployment, but also operating system (currently Open Solaris) deployment on demand. Based on Solaris Jumpstart technology and some related tools, a prototype of this architecture has been developed and running on HPC clusters. With our prototype, the Grid users are able to deploy a basic HPC environment (e.g., OpenSolaris, MPICH, Sun Grid Engine or N1 Grid Engine resource management tool) among the available cluster nodes. Our experiments show that our work provide great convenience and flexibility for users to setup and customize their preferred HPC cluster environment for their computation intensive applications in Grid computing or utility computing.