Parallel algorithm and Time complexity

Shortcuts: Differences, Similarities, Jaccard Similarity Coefficient, References.

Difference between Parallel algorithm and Time complexity

Parallel algorithm vs. Time complexity

In computer science, a parallel algorithm, as opposed to a traditional serial algorithm, is an algorithm which can be executed a piece at a time on many different processing devices, and then combined together again at the end to get the correct result. In computer science, the time complexity is the computational complexity that describes the amount of time it takes to run an algorithm.

Similarities between Parallel algorithm and Time complexity

Parallel algorithm and Time complexity have 3 things in common (in Unionpedia): Algorithm, Computer science, Parallel computing.

Algorithm

In mathematics and computer science, an algorithm is an unambiguous specification of how to solve a class of problems.

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Computer science

Computer science deals with the theoretical foundations of information and computation, together with practical techniques for the implementation and application of these foundations.

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Parallel computing

Parallel computing is a type of computation in which many calculations or the execution of processes are carried out concurrently.

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The list above answers the following questions

What Parallel algorithm and Time complexity have in common
What are the similarities between Parallel algorithm and Time complexity

Parallel algorithm and Time complexity Comparison

Parallel algorithm has 29 relations, while Time complexity has 136. As they have in common 3, the Jaccard index is 1.82% = 3 / (29 + 136).

References

This article shows the relationship between Parallel algorithm and Time complexity. To access each article from which the information was extracted, please visit:

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