Divide-and-conquer has proven to be one of the most powerful techniques for solving problems in parallel with applications ranging from linear systems to computer graphics and from factoring large numbers to n-body simulations. An example grasp is shown. Published in: Robotics and Automation, 1997. Proceedings., 1997 IEEE International Conference on (Volume:1 ) Date of Conference: 20- Page(s vol.1 Meeting Date : -Print ISBN : INSPEC Accession Number: 5678397 Conference Location : Albuquerque, NM DOI: 10.1109/ROBOT.1997.620066 Publisher: IEEE INSPEC : CONTROLLED INDEXING dynamic programming manipulators parallel algorithms. A final consideration is whether the machine supports shared memory, or whether all communication relies on passing messages between the processors. A major advance in parallel algorithms has been the identification of fundamental algorithmic techniques.
We call an algorithm work-efficient (or just efficient) if it performs the same amount of work, to within a constant factor, as the fastest known sequential algorithm. For example, a parallel algorithm that sorts n keys in time using processors is efficient since the work, is as good as any (comparison-based) sequential algorithm.
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Randomization is used to determine the boundaries of the intervals. First each processor selects a random sample of its keys. Next all of the selected keys are sorted together. Finally these keys are used as the boundaries.
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