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Radixsort
In computer science, radix sort is a non-comparative sorting algorithm. It avoids comparison by creating and distributing elements into buckets according to their radix. For elements with more than one significant digit, this bucketing process is repeated for each digit, while preserving the ordering of the prior step, until all digits have been considered. For this reason, radix sort has also been called bucket sort and digital sort. Radix sort can be applied to data that can be sorted lexicographically, be they integers, words, punch cards, playing cards, or the mail. History Radix sort dates back as far as 1887 to the work of Herman Hollerith on tabulating machines. Radix sorting algorithms came into common use as a way to sort punched cards as early as 1923. Donald Knuth. ''The Art of Computer Programming'', Volume 3: ''Sorting and Searching'', Third Edition. Addison-Wesley, 1997. . Section 5.2.5: Sorting by Distribution, pp. 168–179. The first memory-efficient ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Sorting Algorithm
In computer science, a sorting algorithm is an algorithm that puts elements of a list into an order. The most frequently used orders are numerical order and lexicographical order, and either ascending or descending. Efficient sorting is important for optimizing the efficiency of other algorithms (such as search and merge algorithms) that require input data to be in sorted lists. Sorting is also often useful for canonicalizing data and for producing human-readable output. Formally, the output of any sorting algorithm must satisfy two conditions: # The output is in monotonic order (each element is no smaller/larger than the previous element, according to the required order). # The output is a permutation (a reordering, yet retaining all of the original elements) of the input. For optimum efficiency, the input data should be stored in a data structure which allows random access rather than one that allows only sequential access. History and concepts From the beginning of compu ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Counting Sort
In computer science, counting sort is an algorithm for sorting a collection of objects according to keys that are small positive integers; that is, it is an integer sorting algorithm. It operates by counting the number of objects that possess distinct key values, and applying prefix sum on those counts to determine the positions of each key value in the output sequence. Its running time is linear in the number of items and the difference between the maximum key value and the minimum key value, so it is only suitable for direct use in situations where the variation in keys is not significantly greater than the number of items. It is often used as a subroutine in radix sort, another sorting algorithm, which can handle larger keys more efficiently.. See also the historical notes on page 181... Counting sort is not a comparison sort; it uses key values as indexes into an array and the lower bound for comparison sorting will not apply. Bucket sort may be used in lieu of counting sor ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bitonic Sorter
Bitonic mergesort is a parallel algorithm for sorting. It is also used as a construction method for building a sorting network. The algorithm was devised by Ken Batcher. The resulting sorting networks consist of O(n\log^2(n)) comparators and have a delay of O(\log^2(n)), where n is the number of items to be sorted. A sorted sequence is a monotonically non-decreasing (or non-increasing) sequence. A ''bitonic'' sequence is a sequence with x_0 \leq \cdots \leq x_k \geq \cdots \geq x_ for some k, 0 \leq k arr OR (bitwiseAND (i, k) != 0) AND (arr < arr ) swap the elements arr and arr See also *[...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Ken Batcher
Ken Batcher, full name Kenneth Edward Batcher (December 1935 – August 2019) was an emeritus professor of Computer Science at Kent State University. He also worked as a computer architect at Goodyear Aerospace in Akron, Ohio for 28 years. Early life and education He was born in December 1935 in Queens, New York City, to Lois and Ralph Batcher. He died in August 2019 in Stow Ohio. His parents met at Iowa State University and later relocated to New York City after graduation. His father, Ralph R. Batcher, was the Chief Engineer of The A. H. Grebe Radio Company until its bankruptcy in 1932. He graduated from Brooklyn Technical High School. Batcher graduated from Iowa State University with B.E. degree in 1957. In 1964, Batcher received his Ph.D. in electrical engineering from the University of Illinois. His career and achievements Among the designs he worked on at Goodyear were the: * Massively Parallel Processor (16,384 custom bit-serial processors organized in a SIMD 12 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Wojciech Rytter
Wojciech Rytter is a Polish computer scientist, a professor of computer science in the automata theory group at the University of Warsaw. His research focuses on the design and analysis of algorithms, and in particular on stringology, the study of algorithms for searching and manipulating text. Professional career Rytter earned a master's degree in 1971 and a Ph.D. in 1975 from Warsaw University, and earned his habilitation in 1985.Curriculum vitae retrieved 2013-01-15. He has been on the faculty of Warsaw University since 1971, and is now a full professor there.Wojciech Rytter at the |
Parallel Computing
Parallel computing is a type of computation in which many calculations or processes are carried out simultaneously. Large problems can often be divided into smaller ones, which can then be solved at the same time. There are several different forms of parallel computing: bit-level, instruction-level, data, and task parallelism. Parallelism has long been employed in high-performance computing, but has gained broader interest due to the physical constraints preventing frequency scaling.S.V. Adve ''et al.'' (November 2008)"Parallel Computing Research at Illinois: The UPCRC Agenda" (PDF). Parallel@Illinois, University of Illinois at Urbana-Champaign. "The main techniques for these performance benefits—increased clock frequency and smarter but increasingly complex architectures—are now hitting the so-called power wall. The computer industry has accepted that future performance increases must largely come from increasing the number of processors (or cores) on a die, rather tha ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Insertion Sort
Insertion sort is a simple sorting algorithm that builds the final sorted array (or list) one item at a time by comparisons. It is much less efficient on large lists than more advanced algorithms such as quicksort, heapsort, or merge sort. However, insertion sort provides several advantages: * Simple implementation: Jon Bentley shows a three-line C/ C++ version that is five lines when optimized. * Efficient for (quite) small data sets, much like other quadratic (i.e., O(''n''2)) sorting algorithms * More efficient in practice than most other simple quadratic algorithms such as selection sort or bubble sort * Adaptive, i.e., efficient for data sets that are already substantially sorted: the time complexity is O(''kn'') when each element in the input is no more than places away from its sorted position * Stable; i.e., does not change the relative order of elements with equal keys * In-place; i.e., only requires a constant amount O(1) of additional memory space * Online; ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Counting Sort
In computer science, counting sort is an algorithm for sorting a collection of objects according to keys that are small positive integers; that is, it is an integer sorting algorithm. It operates by counting the number of objects that possess distinct key values, and applying prefix sum on those counts to determine the positions of each key value in the output sequence. Its running time is linear in the number of items and the difference between the maximum key value and the minimum key value, so it is only suitable for direct use in situations where the variation in keys is not significantly greater than the number of items. It is often used as a subroutine in radix sort, another sorting algorithm, which can handle larger keys more efficiently.. See also the historical notes on page 181... Counting sort is not a comparison sort; it uses key values as indexes into an array and the lower bound for comparison sorting will not apply. Bucket sort may be used in lieu of counting sor ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Stable Sort
In computer science, a sorting algorithm is an algorithm that puts elements of a list into an order. The most frequently used orders are numerical order and lexicographical order, and either ascending or descending. Efficient sorting is important for optimizing the efficiency of other algorithms (such as search and merge algorithms) that require input data to be in sorted lists. Sorting is also often useful for canonicalizing data and for producing human-readable output. Formally, the output of any sorting algorithm must satisfy two conditions: # The output is in monotonic order (each element is no smaller/larger than the previous element, according to the required order). # The output is a permutation (a reordering, yet retaining all of the original elements) of the input. For optimum efficiency, the input data should be stored in a data structure which allows random access rather than one that allows only sequential access. History and concepts From the beginning of computin ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Lexicographically
In mathematics, the lexicographic or lexicographical order (also known as lexical order, or dictionary order) is a generalization of the alphabetical order of the dictionaries to sequences of ordered symbols or, more generally, of elements of a totally ordered set. There are several variants and generalizations of the lexicographical ordering. One variant applies to sequences of different lengths by comparing the lengths of the sequences before considering their elements. Another variant, widely used in combinatorics, orders subsets of a given finite set by assigning a total order to the finite set, and converting subsets into increasing sequences, to which the lexicographical order is applied. A generalization defines an order on a Cartesian product of partially ordered sets; this order is a total order if and only if all factors of the Cartesian product are totally ordered. Motivation and definition The words in a lexicon (the set of words used in some language) have a co ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Least Significant Digit
Significant figures (also known as the significant digits, ''precision'' or ''resolution'') of a number in positional notation are digits in the number that are reliable and necessary to indicate the quantity of something. If a number expressing the result of a measurement (e.g., length, pressure, volume, or mass) has more digits than the number of digits allowed by the measurement resolution, then only as many digits as allowed by the measurement resolution are reliable, and so only these can be significant figures. For example, if a length measurement gives 114.8 mm while the smallest interval between marks on the ruler used in the measurement is 1 mm, then the first three digits (1, 1, and 4, showing 114 mm) are certain and so they are significant figures. Digits which are uncertain but ''reliable'' are also considered significant figures. In this example, the last digit (8, which adds 0.8 mm) is also considered a significant figure even though ther ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Most Significant Digit
Significant figures (also known as the significant digits, ''precision'' or ''resolution'') of a number in positional notation are digits in the number that are reliable and necessary to indicate the quantity of something. If a number expressing the result of a measurement (e.g., length, pressure, volume, or mass) has more digits than the number of digits allowed by the measurement resolution, then only as many digits as allowed by the measurement resolution are reliable, and so only these can be significant figures. For example, if a length measurement gives 114.8 mm while the smallest interval between marks on the ruler used in the measurement is 1 mm, then the first three digits (1, 1, and 4, showing 114 mm) are certain and so they are significant figures. Digits which are uncertain but ''reliable'' are also considered significant figures. In this example, the last digit (8, which adds 0.8 mm) is also considered a significant figure even though ther ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
