Authors: Angela C. Sodan, Xuemin Huang
Addresses: School of Computer Science, University of Windsor, Ontario N9B 3P4, Canada. ' School of Computer Science, University of Windsor, Ontario N9B 3P4, Canada
Abstract: Time-shared execution of parallel jobs via gang scheduling is known to yield better average response times than space sharing. We incorporate adaptive CPU/node-resource allocation to consider varying system load and to reduce fragmentation. As main innovations, our SCOJO approach provides a clear model how to adapt, and considers realistic job mixes with moldable, malleable and rigid jobs. Our adaptive SCOJO significantly decreases response times and average slowdowns, while using a lower multiprogramming level than standard gang scheduling uses best and, therefore, decreasing the memory pressure. These benefits apply though the realistic job mixes limit the flexibility in resource allocation.
Keywords: job scheduling; parallel systems; adaptive resource allocation; system load adaptation; fragmentation reduction; time sharing; space sharing; high performance computing.
International Journal of High Performance Computing and Networking, 2006 Vol.4 No.5/6, pp.256 - 269
Available online: 01 May 2007 *Full-text access for editors Access for subscribers Purchase this article Comment on this article