Parallel programming with MPI
Using OpenMP: Portable Shared Memory Parallel Programming (Scientific and Engineering Computation)
Using OpenMP: Portable Shared Memory Parallel Programming (Scientific and Engineering Computation)
Prediction models for multi-dimensional power-performance optimization on many cores
Proceedings of the 17th international conference on Parallel architectures and compilation techniques
Validity of the single processor approach to achieving large scale computing capabilities
AFIPS '67 (Spring) Proceedings of the April 18-20, 1967, spring joint computer conference
Hybrid MPI/OpenMP Parallel Programming on Clusters of Multi-Core SMP Nodes
PDP '09 Proceedings of the 2009 17th Euromicro International Conference on Parallel, Distributed and Network-based Processing
Introduction to High Performance Computing for Scientists and Engineers
Introduction to High Performance Computing for Scientists and Engineers
Vascular network modeling: improved parallel implementation on computing cluster
PPAM'09 Proceedings of the 8th international conference on Parallel processing and applied mathematics: Part I
Algorithms and Parallel Computing
Algorithms and Parallel Computing
Vascular System Modeling in Parallel Environment - Distributed and Shared Memory Approaches
IEEE Transactions on Information Technology in Biomedicine
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This paper presents a two-level parallel algorithm of vascular network development. At the outer level, tasks (newly appeared parts of tissue) are spread over processing nodes. Each node attempts to connect/disconnect its assigned parts of tissue in all vascular trees. Communication between nodes is accomplished by a message passing paradigm. At the inner level, subtasks concerning different vascular trees (e.g. arterial and venous) within each task are parallelized by a shared address space paradigm. The solution was implemented on a computing cluster of multi-core nodes with mixed MPI+OpenMP support. The experimental results show that the algorithm provides a significant improvement in computational performance compared with a pure MPI implementation.