Publication | Closed Access
Execution time support for adaptive scientific algorithms on distributed memory machines
70
Citations
10
References
1991
Year
Cluster ComputingEngineeringComputer ArchitectureComputational ComplexityDistributed Data ProcessingAdaptive ComputingParallel SoftwareExecution Time SupportParallel ComputingMassively-parallel ComputingParallelizing CompilerComputer EngineeringComputer ScienceDistributed Memory MachinesCode SegmentsDistributed ProcessingAdaptive Scientific AlgorithmsProgram AnalysisParallel ProcessingCloud ComputingParallel Performance EvaluationParallel ProgrammingData-level ParallelismArray Mappings
Abstract We consider optimizations that are required for efficient execution of code segments that consist of loops over distributed data structures. The PARTI execution time primitives are designed to perform these optimizations and can be used to Implement a wide range of scientific algorithms on distributed memory machines. These primitives allow the user to control array mappings in a way that gives an appearance of shared memory. Computations can be based on a global index set. Primitives are used to perform gather and scatter operations on distributed arrays. Communications patterns are derived at run time, and the appropriate send and receive messages are automatically generated.
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