IEEE Transactions on Parallel and Distributed Systems
The ANL/IBM SP Scheduling System
IPPS '95 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
On the Combined Scheduling of Malleable and Rigid Jobs
SBAC-PAD '04 Proceedings of the 16th Symposium on Computer Architecture and High Performance Computing
Dynamic Malleability in Iterative MPI Applications
CCGRID '07 Proceedings of the Seventh IEEE International Symposium on Cluster Computing and the Grid
Salome platform component model for numerical simulation
COMPSAC '07 Proceedings of the 31st Annual International Computer Software and Applications Conference - Volume 02
A Software Component Model with Spatial and Temporal Compositions for Grid Infrastructures
Euro-Par '08 Proceedings of the 14th international Euro-Par conference on Parallel Processing
Parallel job scheduling — a status report
JSSPP'04 Proceedings of the 10th international conference on Job Scheduling Strategies for Parallel Processing
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Most high-performance computing resource managers only allow applications to request a static allocation of resources. However, evolving applications have resource requirements which change (evolve) during their execution. Currently, such applications are forced to make an allocation based on their peak resource requirements, which leads to an inefficient resource usage. This paper studies whether it makes sense for resource managers to support evolving applications. It focuses on scheduling fully-predictably evolving applications on homogeneous resources, for which it proposes several algorithms and evaluates them based on simulations. Results show that resource usage and application response time can be significantly improved with short scheduling times.