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Regional weather forecasting demands fast simulation over fine-grained grids, resulting in extremely memory- bottlenecked computation, a difficult problem on conventional supercomputers. Early work on accelerating mainstream weather code WRF using GPUs with their high memory performance, however, resulted in only minor speedup due to partial GPU porting of the huge code. Our full CUDA porting of the...
Replication in grid file systems can significantly improve I/O performance of data-intensive applications. However, most of existing replication techniques apply to individual files, which may introduce inefficient replication overheads for a large number of files. We propose a file clustering based replication algorithm for grid file systems. Our algorithm groups files according to a relationship...
Replication in grid file systems can significantly improve I/O performance of data-intensive grid applications, but its manual creation and placement would be impractical in a real grid environment involving thousands to millions of files accessed per application. Although automatic determination of where and how many replicas should be created should be decided with regards to application access...
The performance of MPI collective operations, such as broadcast and reduction, is heavily affected by network topologies, especially in grid environments. Many techniques to construct efficient broadcast trees have been proposed for grids. On the other hand, recent high performance computing nodes are often equipped with multi-lane network interface cards (NICs), most previous collective communication...
Long-running MPI applications on clusters and grids that are prone to node and network failures, motivates the use of fault tolerant MPI implementations. However, previous fault tolerant MPIs lack the ability to allow the user to easily choose appropriate fault recovery strategies according to the execution environment, independent of the application codes-rather, the user often had to hard-code restoration...
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