Job scheduling in the presence of multiple resource requirements
SC '99 Proceedings of the 1999 ACM/IEEE conference on Supercomputing
Characterization and enhancement of Static Mapping Heuristics for Heterogeneous Systems
HiPC '00 Proceedings of the 7th International Conference on High Performance Computing
The Influence of Communication on the Performance of Co-allocation
JSSPP '01 Revised Papers from the 7th International Workshop on Job Scheduling Strategies for Parallel Processing
Local versus Global Schedulers with Processor Co-allocation in Multicluster Systems
JSSPP '02 Revised Papers from the 8th International Workshop on Job Scheduling Strategies for Parallel Processing
Collective bin packing: an active learning exercise
Journal of Computing Sciences in Colleges
Resource Allocation Using Virtual Clusters
CCGRID '09 Proceedings of the 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid
Resource allocation algorithms for virtualized service hosting platforms
Journal of Parallel and Distributed Computing
A CS unplugged activity for the online classroom
Journal of Computing Sciences in Colleges
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Multi-capacity bin-packing is a generalization of the classical one-dimensional bin-packing problem in which the bin capacity and the item sizes are represented by d-dimensional vectors. Previous work in d-capacity bin-packing algorithms analyzed variants of single capacity bin-packing, extended to deal with the d capacities.These extended algorithms are oblivious to the additional capacity information, however, and do not scale well with increasing d. We provide new packing algorithms which use the additional capacity information to provide better packing and show how these algorithms might lead to better multi-resource allocation and scheduling solutions.