By Miller R., Boxer L.
Equip your self for fulfillment with a cutting-edge method of algorithms on hand in simple terms in Miller/Boxer's ALGORITHMS SEQUENTIAL AND PARALLEL: A UNIFIED strategy, 3E. This special and sensible textual content grants an creation to algorithms and paradigms for contemporary computing platforms, integrating the examine of parallel and sequential algorithms inside of a concentrated presentation. With a variety of functional workouts and fascinating examples drawn from primary program domain names, this ebook prepares you to layout, research, and enforce algorithms for contemporary computing platforms
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Additional resources for Algorithms sequential and parallel: a unified approach
It is often possible to modify an algorithm designed for one data structure to accommodate a different data structure. In the exercises, we ask the reader to adapt Insertion Sort to linked lists. EXAMPLE: BIN SORT Sorting is a fundamental operation as a major use of computers is to maintain order within large collections of data. Perhaps for this reason, the computer science community has developed numerous algorithms for ordering data. Some of these algorithms are considerably faster than others in the abstract.
Therefore, if we now add back in the problematic term, we arrive at n n 1 1 = 1 + ≤1+ a a k k=1 k=2 k n ∫1 1 dx = 1 + ln n. x Combining the results of both the upper and lower bounds on f (n), we arrive at n 1 ln n < ln(n + 1) ≤ a ≤ 1 + ln n ≤ 2 ln n k=1 k for n large enough, a conclusion we suggest that the reader verify. Therefore, n 1 a k = Θ(ln n). k=1 Copyright 2013 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s).
In this book, we use the term algorithm to mean a procedure for correctly solving a problem in a finite number of steps. The focus of this book is on the analysis of resources for a reasonable implementation of a given algorithm to solve a given problem correctly. Specifically, the analysis of an algorithm is concerned with estimating resources, such as running time and computer memory, used by the efficient implementation of an algorithm. In general, we will remove the awkwardness of stating “an efficient implementation of an algorithm” and simply assume that the implementation is efficient.