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This form of dynamic dataflow takes advantage of the property that in a large number of image processing applications, data production and consumption rates can vary, but are equal across dataflow graph edges for any particular application iteration.
This, however, has drawbacks, such as forcing the user to manually set the number of iterations (making it impossible for a program to ensure convergence to a given condition), and the re-scheduling overhead of mapping and reduce tasks on every application iteration.
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It points out the inability of Hadoop to directly support iterative parallel applications, thereby requiring a driver program to orchestrate application iterations (each piped as a separate MapReduce job).
Many applications require iteration over elements multiple times.
In the application, 10,000 iterations were performed for each of the burn-in and thereafter.
Application of nonlinear iteration scheme to the nonlinear water wave problem: Stokes wave.
Application of nonlinear iteration scheme to the nonlinear water wave problem: Stokian wave.
Application of variational iteration technique to this problem shows the rapid convergence of the sequence constructed by this method to the exact solution.
Multiset-mappings are introduced to engineer numerical minimization as a repeated application of an iteration mapping.
A popular iterative method is the SIRT method [4], which can be viewed as an application of Landweber iteration [26] to the linear system of tomography.
At each iteration, application of the string method algorithm requires the calculation of the mean force at each image along the string.
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