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At the beginning of this article we claimed that referentially transparent functions can safely be used in parallel algorithms.
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These synchronization protocols, however, are seldom used in parallel algorithm designs, especially for algorithms under the SPMD paradigm, as their implementations are highly hardware dependent and their costs are hard to characterize.
Specifically, lower bounds on execution time independent of the data layout, lower bounds for data layouts in which the number of data items per processor is bounded, and lower bounds for specific data layouts commonly used in designing parallel algorithms for this problem are presented in this paper.
Table 4 shows the extra memory size (in pixels) and the percentage of memory increase for several video frame resolutions and number of processes used in the parallel algorithm.
Additional summary of relevant results in parallel algorithm design and parallel processing machines and languages is presented.
At each step, different parallel strategies are used in algorithm, and the whole algorithm grows fast.
Because of the scale factor and efficiency of the algorithm A †, the new method proposed in this paper can be used in a parallel operation to get a better algorithm.
Using the parallel algorithm considered in [12], we suggest and analyze a parallel iterative method for solving this system.
The first parallelization strategy, which has been used in the existing parallel SFD algorithm on GPU, has the problem of computing redundancy.
The reconfigurable array is used to implement parallels algorithms.
Space-marching techniques may also not be quite as well-suited for the solution of problems involving complex three-dimensional geometries and/or for use in highly-scalable parallel algorithms.
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