Publication | Closed Access
Iterative algorithms for solution of large sparse systems of linear equations on hypercubes
70
Citations
14
References
1988
Year
Numerical AnalysisMathematical ProgrammingEngineeringLarge Sparse SystemsComputer ArchitectureParallel ImplementationParallel AlgorithmsIterative AlgorithmsNumerical ComputationComputing SystemsFinite-element DiscretizationMatrix MethodParallel ComputingApproximation TheoryLow-rank ApproximationComputer EngineeringInverse ProblemsComputer ScienceHypercube TopologyNumerical Method For Partial Differential EquationLinear EquationsSparse RepresentationParallel ProcessingMany-core ArchitectureParallel Programming
Finite-element discretization produces linear equations in the form Ax=b, where A is large, sparse, and banded with proper ordering of the variables x. The solution of such equations on distributed-memory message-passing multiprocessors implementing the hypercube topology is addressed. Iterative algorithms based on the conjugate gradient method are developed for hypercubes designed for coarse-grained parallelism. The communication requirements of different schemes for mapping finite-element meshes onto the processors of a hypercube are analyzed with respect to the effect of communication parameters of the architecture. Experimental results for a 16-node Intel 80386-based iPSC/2 hypercube are presented and discussed.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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