Skip to main content
SpringerLink
Log in

The Rutgers Computational Grid: A Distributed Linux PC Cluster

  • Published:
Cluster Computing Aims and scope Submit manuscript

Abstract

The Rutgers Computational Grid (RCG) project is aimed at providing high throughput performance to Rutgers university faculty and students. The RCG employs dual processor PCs, with Pentium II and III processors, as computational nodes, running the Linux RedHat operating system. The Load Sharing Facility (LSF) scheduling system from Platform Computing is used for job control and monitoring. The nodes are grouped into subclusters physically located in several departments and controlled by a single master node through LSF. The hardware and software used in RCG are described. Utilization and performance issues, including parallel performance, are discussed based on the experience of the first two years of RCG operation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. R.J. Allan, Survey of Computation Grids, Meta-Computers and Network Information Tools ed.2, CLRS Daresbury Laboratory, Daresbury, January 2000.

    Google Scholar 

  2. S. Anasiadis and K. Sevcik, Parallel application scheduler on network of workstations, Journal of Parallel and Distributing Computing 43 (1997) 109-124.

    Google Scholar 

  3. T.E. Anderson, D.E. Culler, D.A. Patterson and the NOWTeam, A case for networks of workstations: NOW, IEEE Micro (February 1995).

  4. R.H. Arpachi, A.C. Dusseau, A.M. Vahdat, L.T. Liu, T.E. Anderson and D.A. Patterson, The interaction of parallel and sequential workloads on a network of workstations, in: Proceedings of ACM SIGMETRICS'95/PERFORMANCE'95 Joint International Conference on Measurement and Modeling of Computer Systems, May 1995, pp. 267-278.

  5. A.C. Arpaci-Dusseau and D.E. Culler, Extending proportional-share scheduling to a network of workstations, in: International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA'97) (1997).

  6. P. Boulet, J. Dongarra, F. Rastello, Y. Pobert and F. Vivien, Algorithmic issues on heterogeneous computer platforms, Parallel Processing Letters 9(2) (1999) 197-213.

    Google Scholar 

  7. R. Buyya, High Performance Computer Clusters: Architecture and Systems, Vol. 1 (Prentice-Hall, NJ, 1999).

    Google Scholar 

  8. J. Dongarra, An overview of computational grids and survey of a few research projects, in: Symposium on Global Information Processing Technology, Japan, 1999.

  9. X. Du and X. Zhang, Coordinating parallel processing on network of workstations, Journal of Parallel and Distributing Computing 46 (1997) 125-135.

    Google Scholar 

  10. I. Foster and C. Kesselman, The Grid: Blueprint for a New Computing Infrastructure (Morgan Kauffman, San Francisco, CA, 1999).

    Google Scholar 

  11. V. Hamscher, U. Schiegelshohn, A. Streit and R. Yahyapour, Evaluation of job-scheduling strategies for grid computing, in: 1st IEEE/ACM International Workshop on Grid Computing, Bangalore, India, 17–;20 December 2000.

  12. G.J. Henry, The fair share scheduler, AT&T Bell Laboratories Technical Journal 63(8) (October 1984) 1845-1857.

    Google Scholar 

  13. http://www.dhpc.adelaide.edu.au/education/honours/campusgrid.html

  14. http://www-isd.fnal.gov/fbatch

  15. J. Kay and P. Lauder, A fair share scheduler, Communications of ACM 31(1) (1988) 44-55.

    Google Scholar 

  16. D. Knight, G. Zhou, N. Okong'o and V. Shukla, Compressible large eddy simulation using unstructured grids, AIAA Paper No. 98-0535, 1998.

  17. Load Sharing Facility, http://www.platform.com

  18. MPICH: A Portable Implementation of MPI, Mathematics and Computer Science Division, Argonne National Lab, http://www-unix.mcs. anl.gov/mpi/mpich/index.html

  19. Rutgers Computational Grid, http://coewww.rutgers.edu/rcg/

Download references

Author information

Authors and Affiliations

  1. Department Mechanical and Aerospace Engineering, Rutgers –; The State University of New Jersey, Piscataway, NJ, USA

    B. Chernyavsky & D. Knight

  2. Department of Chemistry, Rutgers –; The State University of New Jersey, Piscataway, NJ, USA

    E. Gallicchio & R. Levy

  3. Telecommunication Division, Rutgers –; The State University of New Jersey, Piscataway, NJ, USA

    A. Page

Authors
  1. B. Chernyavsky
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. E. Gallicchio
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. D. Knight
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. R. Levy
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. A. Page
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to B. Chernyavsky.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chernyavsky, B., Gallicchio, E., Knight, D. et al. The Rutgers Computational Grid: A Distributed Linux PC Cluster. Cluster Computing 6, 267–278 (2003). https://doi.org/10.1023/A:1023544721955

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1023544721955

Search

Navigation