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Q. Computation step in time complexity of an algorithm?
So First in the computation step the local processor executes an arithmetic and logic operation. Afterwards the several processors communicate with one another for exchanging messages and/or data. Therefore the time complexity can be computed on the grounds of communication cost and computational cost involved. Time complexity of an algorithm fluctuates depending on the instance of input for a provided problem. For illustration the already sorted list (10, 17, 19, 21, 22, 33) will take less amount of time than reverse order of list (33, 22, 21, 19, 17, 10). The time complexity of algorithm has been classified into three forms which are.
i) Best Case Complexity; ii) Average Case Complexity; andiii) Worst Case Complexity.
The best case complexity is the minimum amount of time needed by algorithm for a provided input. The average case complexity is average running time needed by algorithm for a provided input. As in the same manner the worst case complexity is able to be defined as maximum amount of time needed by the algorithm for a provided input. So the major factors occupied for analysing time complexity relies on the algorithm, specific set of inputs and parallel computer model. Mainly the size of input is a function of time complexity of algorithm.
Loop Level At this stage, following loop iterations are candidates for parallel execution. Though, data dependencies among subsequent iterations can restrict parallel execution
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