Guided self-scheduling: A practical scheduling scheme for parallel supercomputers
IEEE Transactions on Computers
Factoring: a method for scheduling parallel loops
Communications of the ACM
Cluster computing: the commodity supercomputer
Software—Practice & Experience
Trapezoid Self-Scheduling: A Practical Scheduling Scheme for Parallel Compilers
IEEE Transactions on Parallel and Distributed Systems
Proceedings of the 2002 ACM/IEEE conference on Supercomputing
A Class of Loop Self-Scheduling for Heterogeneous Clusters
CLUSTER '01 Proceedings of the 3rd IEEE International Conference on Cluster Computing
Beowulf Cluster Computing with Linux
Beowulf Cluster Computing with Linux
Scheduling Divisible Loads on Star and Tree Networks: Results and Open Problems
IEEE Transactions on Parallel and Distributed Systems
An Enhanced Parallel Loop Self-Scheduling Scheme for Cluster Environments
The Journal of Supercomputing
Proceedings of the 2006 ACM/IEEE conference on Supercomputing
Locality and Loop Scheduling on NUMA Multiprocessors
ICPP '93 Proceedings of the 1993 International Conference on Parallel Processing - Volume 02
A performance-based parallel loop scheduling on grid environments
The Journal of Supercomputing
Dynamic partitioning of loop iterations on heterogeneous PC clusters
The Journal of Supercomputing
International Journal of Computational Science and Engineering
Extending FuzzyCLIPS for parallelizing data-dependent fuzzy expert systems
The Journal of Supercomputing
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Recently, a series of parallel loop self-scheduling schemes have been proposed, especially for heterogeneous cluster systems. However, they employed the MPI programming model to construct the applications without considering whether the computing node is multicore architecture or not. As a result, every processor core has to communicate directly with the master node for requesting new tasks no matter the fact that the processor cores on the same node can communicate with each other through the underlying shared memory. To address the problem of higher communication overhead, in this paper we propose to adopt hybrid MPI and OpenMP programming model to design two-level parallel loop self-scheduling schemes. In the first level, each computing node runs an MPI process for inter-node communications. In the second level, each processor core runs an OpenMP thread to execute the iterations assigned for its resident node. Experimental results show that our method outperforms the previous works.