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Full-Text Articles in Physical Sciences and Mathematics
A Comparison Of Optimization Heuristics For The Data Mapping Problem, Nikos Chrisochoides, Nashat Mansour, Geoffrey C. Fox
A Comparison Of Optimization Heuristics For The Data Mapping Problem, Nikos Chrisochoides, Nashat Mansour, Geoffrey C. Fox
Northeast Parallel Architecture Center
In this paper we compare the performance of six heuristics with suboptimal solutions for the data distribution of two dimensional meshes that are used for the numerical solution of Partial Differential Equations (PDEs) on multicomputers. The data mapping heuristics are evaluated with respect to seven criteria covering load balancing, interprocessor communication, flexibility and ease of use for a class of single-phase iterative PDE solvers. Our evaluation suggests that the simple and fast block distribution heuristic can be as effective as the other five complex and computational expensive algorithms.
Mapping Algorithms And Software Environment For Data Parallel, Nikos Chrisochoides, Elias Houstis, John Rice
Mapping Algorithms And Software Environment For Data Parallel, Nikos Chrisochoides, Elias Houstis, John Rice
Northeast Parallel Architecture Center
We consider computations associated with data parallel iterative solvers used for the numerical solution of Partial Differential Equations (PDEs). The mapping of such computations into load balanced tasks requiring minimum synchronization and communication is a difficult combinatorial optimization problem. Its optimal solution is essential for the efficient parallel processing of PDE computations. Determining data mappings that optimize a number of criteria, like workload balance, synchronization and local communication, often involves the solution of an NP-Complete problem. Although data mapping algorithms have been known for a few years there is lack of qualitative and quantitative comparisons based on the actual performance …