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Judy Array
In computer science, a Judy array is an early-2000s Hewlett-Packard hand-optimized implementation of a 256-ary radix tree that uses many situational node types to reduce latency from CPU cache-line fills.Alan Silverstein,Judy IV Shop Manual, 2002 As a compressed radix tree, a Judy array can store potentially sparse integer- or string-indexed data with comparatively low memory usage and low read latency, without relying on hashing or tree balancing, and without sacrificing in-order traversal. Per-operation latency scales as O(\log n)—as expected of a tree—and the leading constant factor is small enough that Judy arrays are suitable even to the peta-element range. When applicable, they can be faster than implementations of AVL trees, B-trees, hash tables, or skip lists from the same time period. History The Judy array was invented by Douglas Baskins over the years leading up to 2002 and named after his sister. Node types Broadly, tree nodes in Judy arrays fall into one of three ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Computer Science
Computer science is the study of computation, information, and automation. Computer science spans Theoretical computer science, theoretical disciplines (such as algorithms, theory of computation, and information theory) to Applied science, applied disciplines (including the design and implementation of Computer architecture, hardware and Software engineering, software). Algorithms and data structures are central to computer science. The theory of computation concerns abstract models of computation and general classes of computational problem, problems that can be solved using them. The fields of cryptography and computer security involve studying the means for secure communication and preventing security vulnerabilities. Computer graphics (computer science), Computer graphics and computational geometry address the generation of images. Programming language theory considers different ways to describe computational processes, and database theory concerns the management of re ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bit Array
A bit array (also known as bitmask, bit map, bit set, bit string, or bit vector) is an array data structure that compactly stores bits. It can be used to implement a simple set data structure. A bit array is effective at exploiting bit-level parallelism in hardware to perform operations quickly. A typical bit array stores ''kw'' bits, where ''w'' is the number of bits in the unit of storage, such as a byte or Word (computer architecture), word, and ''k'' is some nonnegative integer. If ''w'' does not divide the number of bits to be stored, some space is wasted due to Fragmentation (computing), internal fragmentation. Definition A bit array is a mapping from some domain (almost always a range of integers) to values in the set . The values can be interpreted as dark/light, absent/present, locked/unlocked, valid/invalid, et cetera. The point is that there are only two possible values, so they can be stored in one bit. As with other arrays, the access to a single bit can be managed ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bitwise Trie With Bitmap
A bitwise trie is a special form of trie where each node with its child-branches represents a bit sequence of one or more bits of a key. A bitwise trie with bitmap uses a bitmap to denote valid child branches. Tries and bitwise tries A trie is a type of search tree where – unlike for example a B-tree – keys are not stored in the nodes but in the path to leaves. The key is distributed across the tree structure. In a "classic" trie, each node with its child-branches represents one symbol of the alphabet of one position (character) of a key. In bitwise tries, keys are treated as bit-sequence of some binary representation and each node with its child-branches represents the value of a sub-sequence of this bit-sequence to form a binary tree (the sub-sequence contains only one bit) or n-ary tree (the sub-sequence contains multiple bits). To give an example that explains the difference between "classic" tries and bitwise tries: For numbers as keys, the alphabet for a trie could con ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Radix Tree
In computer science, a radix tree (also radix trie or compact prefix tree or compressed trie) is a data structure that represents a space-optimized trie (prefix tree) in which each node that is the only child is merged with its parent. The result is that the number of children of every internal node is at most the radix of the radix tree, where = 2 for some integer ≥ 1. Unlike regular trees, edges can be labeled with sequences of elements as well as single elements. This makes radix trees much more efficient for small sets (especially if the strings are long) and for sets of strings that share long prefixes. Unlike regular trees (where whole keys are compared ''en masse'' from their beginning up to the point of inequality), the key at each node is compared chunk-of-bits by chunk-of-bits, where the quantity of bits in that chunk at that node is the radix of the radix trie. When is 2, the radix trie is binary (i.e., compare that node's 1-bit portion of the key), which mini ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
SIMD
Single instruction, multiple data (SIMD) is a type of parallel computer, parallel processing in Flynn's taxonomy. SIMD describes computers with multiple processing elements that perform the same operation on multiple data points simultaneously. SIMD can be internal (part of the hardware design) and it can be directly accessible through an instruction set architecture (ISA), but it should not be confused with an ISA. Such machines exploit Data parallelism, data level parallelism, but not Concurrent computing, concurrency: there are simultaneous (parallel) computations, but each unit performs exactly the same instruction at any given moment (just with different data). A simple example is to add many pairs of numbers together, all of the SIMD units are performing an addition, but each one has different pairs of values to add. SIMD is particularly applicable to common tasks such as adjusting the contrast in a digital image or adjusting the volume of digital audio. Most modern Cen ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
CPU Cache
A CPU cache is a hardware cache used by the central processing unit (CPU) of a computer to reduce the average cost (time or energy) to access data from the main memory. A cache is a smaller, faster memory, located closer to a processor core, which stores copies of the data from frequently used main memory locations. Most CPUs have a hierarchy of multiple cache levels (L1, L2, often L3, and rarely even L4), with different instruction-specific and data-specific caches at level 1. The cache memory is typically implemented with static random-access memory (SRAM), in modern CPUs by far the largest part of them by chip area, but SRAM is not always used for all levels (of I- or D-cache), or even any level, sometimes some latter or all levels are implemented with eDRAM. Other types of caches exist (that are not counted towards the "cache size" of the most important caches mentioned above), such as the translation lookaside buffer (TLB) which is part of the memory management unit (M ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Trie
In computer science, a trie (, ), also known as a digital tree or prefix tree, is a specialized search tree data structure used to store and retrieve strings from a dictionary or set. Unlike a binary search tree, nodes in a trie do not store their associated key. Instead, each node's ''position'' within the trie determines its associated key, with the connections between nodes defined by individual Character (computing), characters rather than the entire key. Tries are particularly effective for tasks such as autocomplete, spell checking, and IP routing, offering advantages over hash tables due to their prefix-based organization and lack of hash collisions. Every child node shares a common prefix (computer science), prefix with its parent node, and the root node represents the empty string. While basic trie implementations can be memory-intensive, various optimization techniques such as compression and bitwise representations have been developed to improve their efficiency. A n ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Hamming Weight
The Hamming weight of a string (computer science), string is the number of symbols that are different from the zero-symbol of the alphabet used. It is thus equivalent to the Hamming distance from the all-zero string of the same length. For the most typical case, a given set of bits, this is the number of bits set to 1, or the digit sum of the Binary numeral system, binary representation of a given number and the Taxicab geometry, ''ℓ''₁ norm of a bit vector. In this binary case, it is also called the population count, popcount, sideways sum, or bit summation. History and usage The Hamming weight is named after the American mathematician Richard Hamming, although he did not originate the notion. The Hamming weight of binary numbers was already used in 1899 by James Whitbread Lee Glaisher, James W. L. Glaisher to give a formula for Gould's sequence, the number of odd binomial coefficients in a single row of Pascal's triangle. Irving S. Reed introduced a concept, equivalen ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Linear Search
In computer science, linear search or sequential search is a method for finding an element within a list. It sequentially checks each element of the list until a match is found or the whole list has been searched. A linear search runs in linear time in the worst case, and makes at most comparisons, where is the length of the list. If each element is equally likely to be searched, then linear search has an average case of comparisons, but the average case can be affected if the search probabilities for each element vary. Linear search is rarely practical because other search algorithms and schemes, such as the binary search algorithm and hash tables, allow significantly faster searching for all but short lists. Algorithm A linear search sequentially checks each element of the list until it finds an element that matches the target value. If the algorithm reaches the end of the list, the search terminates unsuccessfully. Basic algorithm Given a list of elements with values ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Hewlett-Packard
The Hewlett-Packard Company, commonly shortened to Hewlett-Packard ( ) or HP, was an American multinational information technology company. It was founded by Bill Hewlett and David Packard in 1939 in a one-car garage in Palo Alto, California, where the company would remain headquartered for the remainder of its lifetime; this HP Garage is now a designated landmark and marked with a plaque calling it the "Birthplace of 'Silicon Valley. HP developed and provided a wide variety of hardware components, as well as software and related services, to consumers, small and medium-sized businesses (small and medium-sized enterprises, SMBs), and fairly large companies, including customers in government sectors, until the company officially split into Hewlett Packard Enterprise and HP Inc. in 2015. HP initially produced a line of electronic test and measurement equipment. It won its first big contract in 1938 to provide the HP 200B, a variation of its first product, the HP 200A low-distor ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Association List
In computer programming and particularly in Lisp, an association list, often referred to as an alist, is a linked list in which each list element (or node) comprises a key and a value. The association list is said to ''associate'' the value with the key. In order to find the value associated with a given key, a sequential search is used: each element of the list is searched in turn, starting at the head, until the key is found. Associative lists provide a simple way of implementing an associative array, but are efficient only when the number of keys is very small. Operation An associative array is an abstract data type that can be used to maintain a collection of key–value pairs and look up the value associated with a given key. The association list provides a simple way of implementing this data type. To test whether a key is associated with a value in a given association list, search the list starting at its first node and continuing either until a node containing the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Skip List
In computer science, a skip list (or skiplist) is a Randomized algorithm, probabilistic data structure that allows O(\log n) Average-case complexity, average complexity for search as well as O(\log n) average complexity for insertion within an ordered sequence of n elements. Thus it can get the best features of a sorted Array data structure, array (for searching) while maintaining a linked list-like structure that allows insertion, which is not possible with a static array. Fast search is made possible by maintaining a linked hierarchy of subsequences, with each successive subsequence skipping over fewer elements than the previous one (see the picture below on the right). Searching starts in the sparsest subsequence until two consecutive elements have been found, one smaller and one larger than or equal to the element searched for. Via the linked hierarchy, these two elements link to elements of the next sparsest subsequence, where searching is continued until finally searching in ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
