Multi-domain job coscheduling for leadership computing systems

Current supercomputing centers usually deploy a large-scale compute system together with an associated data analysis or visualization system. Multiple scenarios have driven the demand that some associated jobs co-execute on different machines. We propose a multi-domain coscheduling mechanism, providing the ability to coordinate execution between jobs on multiple resource management domains without manual intervention. We have evaluated our mechanism based on real job traces from Intrepid and Eureka, the production Blue Gene/P system and a cluster with the largest GPU installation, deployed at Argonne National Laboratory. The experimental results show that coscheduling can be achieved with limited impact on system performance under varying workloads.

[1]  Klara Nahrstedt,et al.  A distributed resource management architecture that supports advance reservations and co-allocation , 1999, 1999 Seventh International Workshop on Quality of Service. IWQoS'99. (Cat. No.98EX354).

[2]  Warren Smith,et al.  A Resource Management Architecture for Metacomputing Systems , 1998, JSSPP.

[3]  Dror G. Feitelson,et al.  Flexible coscheduling: mitigating load imbalance and improving utilization of heterogeneous resources , 2003, Proceedings International Parallel and Distributed Processing Symposium.

[4]  Michael E. Papka,et al.  Toward simulation-time data analysis and I/O acceleration on leadership-class systems , 2011, 2011 IEEE Symposium on Large Data Analysis and Visualization.

[5]  Sathish S. Vadhiyar,et al.  A metascheduler for the Grid , 2002, Proceedings 11th IEEE International Symposium on High Performance Distributed Computing.

[6]  Michael E. Papka,et al.  Topology-aware data movement and staging for I/O acceleration on Blue Gene/P supercomputing systems , 2011, 2011 International Conference for High Performance Computing, Networking, Storage and Analysis (SC).

[7]  Eduardo Huedo,et al.  A framework for adaptive execution in grids , 2004, Softw. Pract. Exp..

[8]  Dan Tsafrir,et al.  Backfilling Using System-Generated Predictions Rather than User Runtime Estimates , 2007, IEEE Transactions on Parallel and Distributed Systems.

[9]  John K. Ousterhout.  Scheduling Techniques for Concurrebt Systems. , 1982, ICDCS 1982.

[10]  Zhiling Lan,et al.  Fault-aware, utility-based job scheduling on Blue, Gene/P systems , 2009, 2009 IEEE International Conference on Cluster Computing and Workshops.

[11]  Miron Livny,et al.  Improving Goodput by Coscheduling CPU and Network Capacity , 1999, Int. J. High Perform. Comput. Appl..

[12]  Patrick Sobalvarro,et al.  Demand-Based Coscheduling of Parallel Jobs on Multiprogrammed Multiprocessors , 1995, JSSPP.

[13]  Zhiling Lan,et al.  Analyzing and adjusting user runtime estimates to improve job scheduling on the Blue Gene/P , 2010, 2010 IEEE International Symposium on Parallel & Distributed Processing (IPDPS).

[14]  Ibm Blue,et al.  Overview of the IBM Blue Gene/P Project , 2008, IBM J. Res. Dev..

[15]  Wu-chun Feng,et al.  Buffered coscheduling: a new methodology for multitasking parallel jobs on distributed systems , 2000, Proceedings 14th International Parallel and Distributed Processing Symposium. IPDPS 2000.

[16]  Arie Shoshani,et al.  Co-Scheduling of Computation and Data on Computer Clusters , 2005, SSDBM.

[17]  Dan Tsafrir,et al.  A Short Survey of Commercial Cluster Batch Schedulers , 2005 .

[18]  Karsten Schwan,et al.  DataStager: scalable data staging services for petascale applications , 2009, HPDC '09.

[19]  John K. Ousterhout,et al.  Scheduling Techniques for Concurrent Systems , 1982, ICDCS.

[20]  Scott Pakin,et al.  Dynamic Coscheduling on Workstation Clusters , 1998, JSSPP.

[21]  Metin Nafi Gürcan,et al.  Coordinating the use of GPU and CPU for improving performance of compute intensive applications , 2009, 2009 IEEE International Conference on Cluster Computing and Workshops.

[22]  Anshu Dubey,et al.  Large-scale simulations of buoyancy-driven turbulent nuclear burning , 2008 .

[23]  Dror G. Feitelson,et al.  Paired Gang Scheduling , 2003, IEEE Trans. Parallel Distributed Syst..

[24]  Phil Andrews,et al.  Co-scheduling with User-Settable Reservations , 2005, JSSPP.

[25]  Warren Smith,et al.  Scheduling with advanced reservations , 2000, Proceedings 14th International Parallel and Distributed Processing Symposium. IPDPS 2000.

[26]  Jon MacLaren,et al.  HARC: The Highly-Available Resource Co-allocator , 2007, OTM Conferences.

[27]  Zhiling Lan,et al.  Job Coscheduling on Coupled High-End Computing Systems , 2011, 2011 40th International Conference on Parallel Processing Workshops.

[28]  Michael E. Papka,et al.  Developing a Distributed Collaborative Radiological Visualization Application , 2005, HealthGrid.