Modelling the Behaviour of an Adaptive Scheduling Controller

The deployment, management and total cost of ownership of large computing environments always involve huge investments. These systems, once in production, have to meet the needs of users belonging to large and heterogeneous communities: only an efficient and effective use of these systems can repay the investment made. The heterogeneity of user communities implies that computational resources are used for different type of applications, traditional (sequential) or HPC (MPI and Open MP based), whose demands are often conflicting. In this document we report experiences in designing, implementing and validating an adaptive scheduling controller (ASC) that, by using an "adaptive" approach in scheduling policy, allows a balanced, effective and efficient use of computational resources.

[1]  Francesco Palmieri,et al.  GMPLS-based service differentiation for scalable QoS support in all-optical Grid applications , 2006, Future Gener. Comput. Syst..

[2]  Giuseppe Serazzi,et al.  Adaptive Optimization of a System's Load , 1984, IEEE Transactions on Software Engineering.

[3]  Francesco Palmieri,et al.  Network-aware scheduling for real-time execution support in data-intensive optical Grids , 2009, Future Gener. Comput. Syst..

[4]  Amril Nazir,et al.  Cost-benefit analysis of high performance computing infrastructures , 2010, 2010 IEEE International Conference on Service-Oriented Computing and Applications (SOCA).

[5]  Ian Foster,et al.  Designing and building parallel programs , 1994 .

[6]  Luisa Carracciuolo,et al.  HADAB: Enabling Fault Tolerance in Parallel Applications Running in Distributed Environments , 2011, PPAM.

[7]  Luisa Carracciuolo,et al.  Toward a Flexible, Environmentally Conscious, on Demand High Performance Computing Service , 2011, 2011 First International Conference on Data Compression, Communications and Processing.

[8]  Uwe Schwiegelshohn,et al.  Theory and Practice in Parallel Job Scheduling , 1997, JSSPP.

[9]  Thomas L. Casavant,et al.  A Taxonomy of Scheduling in General-Purpose Distributed Computing Systems , 1988, IEEE Trans. Software Eng..

[10]  Adrian T. Wong Evaluating system effectiveness in high performance computing systems , 1999 .

[11]  Fatos Xhafa,et al.  Meeting security and user behavior requirements in Grid scheduling , 2011, Simul. Model. Pract. Theory.

[12]  Fatos Xhafa,et al.  Modern approaches to modeling user requirements on resource and task allocation in hierarchical computational grids , 2011, Int. J. Appl. Math. Comput. Sci..

[13]  Wen-Jing Hsu,et al.  Fair and Efficient Online Adaptive Scheduling for Multiple Sets of Parallel Applications , 2011, 2011 IEEE 17th International Conference on Parallel and Distributed Systems.

[14]  Mark J. Clement,et al.  Core Algorithms of the Maui Scheduler , 2001, JSSPP.