Using dual approximation algorithms for scheduling problems theoretical and practical results
Journal of the ACM (JACM)
UET scheduling with unit interprocessor communication delays
Discrete Applied Mathematics
Approximate algorithms scheduling parallelizable tasks
SPAA '92 Proceedings of the fourth annual ACM symposium on Parallel algorithms and architectures
Algorithms for scheduling malleable and nonmalleable parallel tasks
Algorithms for scheduling malleable and nonmalleable parallel tasks
A Strip-Packing Algorithm with Absolute Performance Bound 2
SIAM Journal on Computing
Efficient approximation algorithms for scheduling malleable tasks
Proceedings of the eleventh annual ACM symposium on Parallel algorithms and architectures
Linear-time approximation schemes for scheduling malleable parallel tasks
Proceedings of the tenth annual ACM-SIAM symposium on Discrete algorithms
Parallel Computer Architecture: A Hardware/Software Approach
Parallel Computer Architecture: A Hardware/Software Approach
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Parallel Real Root Isolation Using the Descartes Method
HiPC '99 Proceedings of the 6th International Conference on High Performance Computing
Theory and Practice in Parallel Job Scheduling
IPPS '97 Proceedings of the Job Scheduling Strategies for Parallel Processing
Dynamic Load Balancing for Ocean Circulation Model with Adaptive Meshing
Euro-Par '99 Proceedings of the 5th International Euro-Par Conference on Parallel Processing
Adaptive time/space sharing with SCOJO
International Journal of High Performance Computing and Networking
Adaptive job scheduling via predictive job resource allocation
JSSPP'06 Proceedings of the 12th international conference on Job scheduling strategies for parallel processing
Hierarchical scheduling for moldable tasks
Euro-Par'05 Proceedings of the 11th international Euro-Par conference on Parallel Processing
Job scheduling using successive linear programming approximations of a sparse model
Euro-Par'12 Proceedings of the 18th international conference on Parallel Processing
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The model of malleable task (MT) was introduced some years ago and has been proved to be an efficient way for implementing parallel applications. It considers a target application at a larger level of granularity than in other models (corresponding typically to numerical routines) where the tasks can themselves be executed in parallel.Clusters of SMP (symmetric Multi-Processors) are a cost effective alternative to parallel supercomputers. Such hierarchical clusters are parallel systems made from m SMP composed each by k identical processors. They are more and more popular, however, designing efficient software that tale full advantage of such systems remains difficult. This work describes a 2 — 2÷k approximation algorithm for scheduling a set of independent malleable tasks for the minimization of the parallel execution time, where k is a power of 2 (k 2). For k = 2, a special treatment leads to the bound of 3/2 which is the best known for non hierarchical tasks. The algorithm presented here is a fully polynomial approximation scheme running in &Ogr;(nmk) time.