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    If a parallel algorithm achieves speedup only by employin... — Carmelics
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    Supports→Parallel algorithms that require exponentially many processors relative to input size are of little practical significance

    If a parallel algorithm achieves speedup only by employing exponentially many processors relative to input size, there is little hope of building a concrete computing device to implement it

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    SkepticismTruth & Knowledge

    Key Terms

    Concrete computing device(as used in computer science and philosophy of technology)
    An actual, physical machine or computer that you can build and use in the real world, as opposed to something that only works in theory.
    Exponentially(as used in mathematics and chaos theory)
    Growing or increasing at an accelerating rate, like doubling again and again—so small differences become huge ones very quickly.
    Input size

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    Related propositions within the same area of thought.
    (as used in computer science)
    How much data or how many items a program needs to process; for example, the number of items in a list you're sorting.
    Parallel algorithm(computer science/computational theory)
    A set of computational steps designed to be executed simultaneously across multiple processors or computers working together, rather than one after another on a single processor.
    Processors(as used in computer science)
    The computing chips or units that actually do the calculations and execute instructions in a computer.
    Speedup(as used in computer science)
    How much faster a computation gets done when you use multiple processors working together compared to using just one.

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    Parallel algorithms that require exponentially many processors relative to input...

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    If parallel algorithms achieve speedup only at the cost of exponential...98%If a parallel algorithm requires exponentially many processors relativ...95%If parallel speedup requires exponentially many processors relative to...94%Parallel algorithms that achieve speedup only by employing exponential...89%

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    AI-extracted
    SEP: computational-complexity
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    Consider, for instance the following variation on the standard rules of Go: (i) the game is played on an \(n \times n\) board; (ii) the winner of the game is the player with the most stones at the end of \(n^2\) rounds. e. the player who moves first)? [30] What these games have in common is that the definition of a winning strategy for the player who moves first involves the alternation of existential and universal quantifiers in a manner which mimics the definition of the classes \(\Sigma^P_n\)

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