Lead rewrite date April 2011 Image Euclid flowchart 1.png 200px thumb lright Flow chart of an algorithm Euclid s algorithm for calculating the greatest common divisor g.c.d. of two numbers a and b in locations named A and B. The algorithm proceeds by successive subtractions in two loops IF the test B ... a in location A THEN the algorithm specifies B B A meaning the number b a replaces the old b . Similarly IF A B THEN A A B. The process terminates when the contents of B is 0, yielding the g.c.d. in A. Algorithm ... and computer science , an algorithm IPAc en audio en us algorithm.ogg l r m from Algoritmi ... are used for calculation , data processing , and automated reasoning . More precisely, an algorithm is an effective method expressed as a finite list ref Any classical mathematical algorithm, for example ... instructions ref Well defined with respect to the agent that executes the algorithm There is a computing ... 1987 2 . ref for calculating a Function mathematics function . ref an algorithm is a procedure for computing ... and initial input perhaps null string empty , ref An algorithm has zero or more inputs, i.e., quantity quantities which are given to it initially before the algorithm begins Knuth 1973 5 . ref the instructions ... ref A procedure which has all the characteristics of an algorithm except that it possibly lacks ... states, eventually producing output ref An algorithm has one or more outputs, i.e. quantities which ... processes not including the input is an algorithm is debatable. Rogers opines that a computation ... Moschovakis chapter What is an algorithm? title Mathematics Unlimited &mdash 2001 and beyond editor1 ... definition For a detailed presentation of the various points of view around the definition of algorithm see Algorithm characterizations . For examples of simple addition algorithms specified in the detailed manner described in Algorithm characterizations , see Algorithm examples . While there is no generally accepted formal definition of algorithm, an informal definition could be a set of rules ... more details
Algorithm design is a specific method to create a mathematical process in solving problems. Applied algorithm design is algorithm engineering . Algorithm design is identified and incorporated into many solution theories of operation research , such as dynamic programming and Divide and conquer algorithm divide and conquer . Techniques for designing and implementing algorithm designs are algorithm design patterns, ref citation url http ww3.algorithmdesign.net ch00 front.html title Algorithm Design Foundations, Analysis, and Internet Examples last1 Goodrich first1 Michael T. author1 link Michael T. Goodrich last2 Tamassia first2 Roberto author2 link Roberto Tamassia publisher John Wiley & Sons, Inc. year 2002 isbn 0 471 38365 1 ref such as template method pattern and decorator pattern , and uses of data structures, and name and sort lists. Some current day uses of algorithm design can be found in internet retrieval processes of web crawling, packet routing and caching. Mainframe programming languages such as ALGOL for Algo rithmic l anguage , FORTRAN , COBOL , PL I, SAIL programming language SAIL , and SNOBOL are computing tools to implement an algorithm design ... but, an algorithm design a d is not a language. An a d can be a hand written process, e.g. set of equations, a series of mechanical processes done by hand, an analog piece of equipment, or a digital process and or processor. One of the most important aspects of algorithm design is creating an algorithm that has an efficient run time, also known as its big Oh . Famous algorithms Dijkstra s algorithm Kruskal s algorithm Quicksort Merge sort Depth first search Breadth search Insertion sort Notes reflist Further reading http www.csc.liv.ac.uk ped teachadmin algor algor.html Algorithm Design Paradigms Overview by Paul Dunne at the University of Liverpool http www.cs.sunysb.edu algorith Stony Brook Algorithm Repository ... Algorithm Design Category Algorithms Category Operations research Mathanalysis stub fa ... more details
Robinson algorithm may refer to Robinson s Resolution Algorithm Robinson Schensted correspondence Robinson s unification algorithm mathdab Short pages monitor This long comment was added to the page to prevent it being listed on Special Shortpages. It and the accompanying monitoring template were generated via Template Longcomment. Please do not remove the monitor template without removing the comment as well. ... more details
Sequential algorithm can refer to, in general, any algorithm executed sequentially, but, specifically, one for decoding a convolutional code ref cite web url http www.encyclopedia.com doc 1O11 sequentialalgorithm.html title A Dictionary of Computing at Encyclopedia.com ref . References reflist Category Algorithms algorithm stub kk ... more details
In computer science, a stable sorting algorithm preserves the order of records with equal keys. In numerical analysis, a numerical stability numerically stable algorithm avoids magnifying small errors. See also Stable disambiguation Stability disambiguation disambig ... more details
Consensus algorithm may refer to one of several proposed protocols for solving the Consensus computer science consensus problem in the field of Computer Science. Some of these include Paxos computer science Chandra Toueg consensus algorithm disambig ... more details
Chaitin s algorithm is a bottom up, graph coloring register allocation algorithm that uses cost degree as its spill metric . It is named after its designer, Gregory Chaitin . Chaitin s algorithm was the first register allocation algorithm that made use of coloring of the interference graph for both register allocations and spilling. Chaitin s algorithm was presented on the 1982 SIGPLAN Symposium on Compiler Construction, and published in the symposium proceedings. It was extension of an earlier 1981 paper on the use of graph coloring for register allocation. Chaitin s algorithm formed the basis of a large section of research into register allocators. References http portal.acm.org citation.cfm?id 989403 Gregory Chaitin Register allocation and spilling via graph coloring http www.cs.utexas.edu pingali CS380C 2010 papers p66 chaitin.pdf Gregory Chaitin Register allocation and spilling via graph coloring Category Graph algorithms ... more details
Distinguish Forward backward algorithm The forward algorithm , in the context of a hidden Markov model , is used to calculate a belief state the probability of a state at a certain time, given the history of evidence. The process is also known as filtering . The forward algorithm is closely related to, but distinct from, the Viterbi algorithm . For an HMM such as this one Image hmm temporal bayesian net.svg 300px center Temporal evolution of a hidden Markov model this probability is written as math P x t y 1 t math . abbreviating math x t math as math x t math . A belief state can be calculated at each time step, but doing this does not, in a strict sense, produce the most likely state sequence . but rather the most likely state at each time step, given the previous history. Smoothing In order to take into account future history i.e., if one wanted to improve the estimate for past times , you can run the Backward algorithm, a complement of the Forward. This is called smoothing . Mathematically, it would be said that the forward backward algorithm computes math P x k y 1 t math for math 0 k t math . So the use of the full F B algorithm takes into account all evidence. Decoding In order to achieve the most likely sequence, the Viterbi algorithm is required. It computes the most likely state sequence given the history of observations, that is, the state sequence that maximizes math P x 0 t y 0 t math . The difference between the state sequence that the Viterbi algorithm estimate generates and the state sequence that the Forward algorithm generates is that the Viterbi algorithm recalculates the entire sequence with each new data point whereas the Forward Algorithm only appends the new current value to the previous sequence computed. See also Viterbi algorithm Forward backward algorithm Further reading Russel and Norvig s Artificial Intelligence, a Modern Approach , starting on page 541 of the 2003 edition, provides a succinct exposition of this and related topics algorithm ... more details
Image Algorithm engineering.svg thumb Algorithm engineering is a combination of theoretical algorithm design with real world data. By taking an algorithm and combining it with a hardware device connected to the real world, you are able to more accurately verify and validate the algorithm results and behavior. The real world device may be a simple data acquisition or stimulus device or you may take the algorithm and implement it on some embedded platform such as an FPGA or microprocessor that may be similar to the final system design. The term algorithm engineering was first used with specificity in 1997, with the organization of the first Workshop on Algorithm Engineering WAE97 ref http www.dsi.unive.it wae97 Workshop on Algorithm Engineering ref . It has recently been used to help describe ... algorithm engineering with respect to Electronic system level ESL . blockquote Algorithm engineering refers to the process required to transform a pencil and paper algorithm into a robust ..., is experimentation. Algorithm Engineering for Parallel Computation David A. Bader , Bernard M. E. Moret, and Peter Sanders ref http lcbb.epfl.ch moret dagstuhl2.pdf Algorithm Engineering for Parallel Computation ref blockquote Conferences Some annual conferences have been held for algorithm engineering Workshop on Algorithm Engineering WAE , since 1997. Workshop on Algorithm Engineering and Experimentation ALENEX , since 1999. The 1997 Workshop on Algorithm Engineering WAE 97 was held in Venice Italy on September 11 13, 1997. The Third International Workshop on Algorithm Engineering WAE 99 was held in London, UK in July 1999. ref Algorithm engineering 3rd International Workshop , Jeffrey Scott ... BGoogle sC . ref The first Workshop on Algorithm Engineering and Experimentation ALENEX99 was held in Baltimore, Maryland on January 15 16, 1999. ref name jhu Workshop on Algorithm Engineering ... showArticle.jhtml?articleID 197008806 Embedded.com DEFAULTSORT Algorithm Engineering Category Operations ... more details
In computer science , an online algorithm is one that can process its input piece by piece in a serial fashion, i.e., in the order that the input is fed to the algorithm, without having the entire input available from the start. In contrast, an offline algorithm is given the whole problem data from the beginning and is required to output an answer which solves the problem at hand. For example, selection sort requires that the entire list be given before it can sort it, while insertion sort doesn t. Because it does not know the whole input, an online algorithm is forced to make decisions that may later turn out not to be optimal, and the study of online algorithms has focused on the quality of decision making that is possible in this setting. Competitive analysis online algorithm Competitive analysis formalizes this idea by comparing the relative performance of an online and offline algorithm for the same problem instance. For other points of view on online inputs to algorithms, see streaming algorithm focusing on the amount of memory needed to accurately represent past inputs , dynamic algorithm focusing on the time complexity of maintaining solutions to problems with online inputs ..., the offline algorithm knows in advance which edges will fail and the goal is to minimize the ratio ... Balance2 Online algorithm BALANCE2 Balance Slack Online algorithm BALANCE SLACK Double Coverage Online algorithm Double Coverage Equipoise Online algorithm EQUIPOISE Handicap Online algorithm HANDICAP Harmonic Online algorithm HARMONIC Random Slack Online algorithm RANDOM SLACK Tight Span Algorithm Online algorithm Tight Span Algorithm Tree Algorithm Online algorithm Tree Algorithm Work Function Algorithm WFA See also Greedy algorithm Adversary online algorithm Adversary Model Job Shop Scheduling Job shop scheduling List update problem Metrical task systems Odds algorithm Page replacement algorithm ... Search games Algorithms for calculating variance Bandit problem Ukkonen s algorithm References cite ... more details
Multiple issues context October 2009 notability October 2009 unreferenced October 2009 The false nearest neighbor FNN algorithm is an algorithm for estimating the embedding dimension . See also Time series Nearest neighbor References cite doi 10.1016 S0098 1354 97 87657 0 cite doi 10.1103 PhysRevE.60.4970 Category Statistical algorithms Category Dynamical systems Category Nonlinear time series analysis algorithm stub ... more details
Raymond s Algorithm is a token based algorithm for mutual exclusion on a distributed system . It imposes a logical structure a K ary tree on distributed resources. As defined, each node has only a single parent, to which all requests to attain the token are made. Algorithm Nodal Properties Each node has only one parent to whom received requests are forwarded Each node maintains a FIFO queue of requests Each node forwards only a single request for each time that it sees the token Algorithm If a node i wishes to receive the token in order to enter into its critical section , it sends a request to its parent, node j . If node j FIFO is empty, node j shifts i into the its FIFO queue j then issues a request to its parent, k , that it desires the token If node j FIFO queue is not empty, it simply shifts i into the queue When node j receives the token from k , it forwards the token to i and i is removed from the queue of j If the queue of j is not empty after forwarding the token to i , j must issue a request to i in order to get the token back Note If j wishes to request a token, and its queue is not empty, then it places itself into its own queue. Node j will utilize the token to enter into its critical section if it is at the head of the queue when the token is received. Complexity Raymond s algorithm is guaranteed to be O log n per critical section entry if the processors are organized into a K ary tree. Additionally, each processor needs to store at most O log n bits because it must track O 1 neighbors. ref R. Chow, T. Johnson Distributed Operating Systems & Algorithms Addison Wesley, 1997. ref References references See also Ricart Agrawala algorithm Lamport s bakery algorithm Lamport s Bakery Algorithm Lamport s Distributed Mutual Exclusion Algorithm Maekawa s Algorithm Suzuki Kasami s Algorithm Naimi Trehel s Algorithm Category Concurrency control algorithms ... more details
In computer science , a nondeterministic algorithm is an algorithm that can exhibit different behaviors on different runs, as opposed to a deterministic algorithm . There are several ways an algorithm may behave differently from run to run. A concurrent algorithm can perform differently on different runs due to a race condition . A probabalistic algorithm s behaviors depends on a random number generator . An algorithm that solves a problem in nondeterministic polynomial time can run in polynomial ... theory , the term algorithm refers to a deterministic algorithm . A nondeterministic algorithm ... various routes. If a deterministic algorithm represents a single path from an input to an outcome, a nondeterministic algorithm represents a single path stemming into many paths, some of which may ... . In algorithm design, nondeterministic algorithms are often used when the problem solved by the algorithm ... algorithm produces is valid, regardless of which choices the algorithm makes while running ... nondeterministic algorithms with deterministic ones One way to simulate a nondeterministic algorithm N using a deterministic algorithm D is to treat sets of states of N as states of D . This means that D ... in use for finite automata . Another is Randomized algorithm randomization , which consists ... deterministic algorithm. Examples Example 1 Merge sort Suppose we have a finite collection of things say, 300 student exams that we need to sort say, by student number . One algorithm to do this called ... if it connects all of its nodes. The algorithm while an edge can be removed such that the graph ... itself allows multiple possible outcomes, and the algorithm chosen can arrive at any one of them, but will never arrive at something else. This is, again, an algorithm that always arrives at a correct ... two, determine whether it is prime number prime . A nondeterministic algorithm for this problem ... . If this algorithm returns the answer composite then the number is certainly not prime. If the algorithm ... more details
Unreferenced date December 2009 Disputed date March 2008 In statistical mechanics , the Gibbs algorithm , first introduced by J. Willard Gibbs in 1878, is the injunction to choose a statistical ensemble probability distribution for the unknown microstate statistical mechanics microscopic state of a thermodynamic system by minimising the average log probability math H sum i p i ln p i , math subject to the probability distribution satisfying a set of constraints usually expectation values corresponding to the known macroscopic quantities. Physicists call the result of applying the Gibbs algorithm the Gibbs distribution for the given constraints, most notably Gibbs s grand canonical ensemble for open systems when the average energy and the average number of particles are given. See also Partition function mathematics partition function . In the light of Claude E. Shannon Claude Shannon s information theory , in 1957 E.T. Jaynes re interpreted the Gibbs algorithm as a much more general, more widely applicable inference technique, leading to the principle of maximum entropy , and the Maximum entropy thermodynamics MaxEnt view of thermodynamics . This general result of the Gibbs algorithm is then a maximum entropy probability distribution . Statisticians identify such distributions as belonging to exponential family exponential families . Not to be confused with The Gibbs sampler , an update algorithm used in Markov chain Monte Carlo iterations, a special case of the Metropolis Hastingsalgorithm . DEFAULTSORT Gibbs Algorithm Category Statistical mechanics Category Particle statistics Category Entropy and information ... more details
Context date August 2010 Pantelides algorithm gives a systematic method for reducing high index systems of Differential algebraic equation differential algebraic equations to lower index, by selectively adding differentiated forms of the equations already present in the system. ref C Pantelides, http dx.doi.org 10.1137 0909014 The Consistent Initialization of Differential Algebraic Systems , SIAM J. Sci. and Stat. Comput. Volume 9, Issue 2, pp. 213 231 March 1988 the original paper where the algorithm is described ref ref Francois Cellier, http www.ece.arizona.edu cellier ece449 lecture.html Lecture notes about Pantelides algorithm ref ref John Pye, http jpye.dyndns.org pantelides Pantelides Algorithm in PHP source code in PHP language ref It is possible for the algorithm to fail in some instances. Pantelides algorithm is implemented in several significant equation based simulation programs such as gPROMS, Modelica and EMSO. ref Peter A. Fritzson, Principles of Object Oriented Modeling and Simulation with Modelica 2.1 , Wiley, ISBN 0471471631 ref ref R de P. Soares and A R. Secchi, 2005, Direct initialisation and solution of high index DAE systems , Computer Aided Chemical Engineering 20 , doi 10.1016 S1570 7946 05 80148 8 . ref ref http www.enq.ufrgs.br trac alsoc wiki EMSO EMSO a free to use closed source simulator equation solver that includes implementation for the Pantelides algorithm. ref Further reading references math stub date March 2009 Category Numerical differential equations ... more details
Mergeto Forward backward algorithm discuss Talk Forward backward algorithm Merger proposal date June 2009 The BCJR algorithm is an algorithm for maximum a posteriori decoding of error correcting code s defined on trellises principally convolutional code s . The algorithm is named after its inventors Bahl, Cocke, Frederick Jelinek Jelinek and Raviv ref name bcjr L.Bahl, J.Cocke, F.Jelinek, and J.Raviv, Optimal Decoding of Linear Codes for minimizing symbol error rate , IEEE Transactions on Information Theory, vol. IT 20 2 , pp.284 287, March 1974. ref . This algorithm is critical to modern iteratively decoded error correcting codes including turbo code s and low density parity check code s. Steps involved based on the convolutional code trellis Compute Forward probabilities math alpha math Compute Backward probabilities math beta math Compute smoothed probabilities based on other information i.e. noise variance for AWGN , bit crossover probability for Binary symmetric channel Variations SBGT BCJR Berrou, Glavieux and Thitimajshima Simplification ref Sichun Wang and Fran ois Patenaude, A Systematic Approach to Modified BCJR MAP Algorithms for Convolutional Codes, EURASIP Journal on Applied Signal Processing , vol. 2006, Article ID 95360, 15 pages, 2006. doi 10.1155 ASP 2006 95360 ref . Log Map BCJR ref P. Robertson, P. Hoeher and E. Villebrun, Optimal and Sub Optimal Maximum A Posteriori Algorithms Suitable for Turbo Decoding , European Transactions on Telecommunications, Vol. 8, 1997. ref Max Log Map BCJR See also Forward backward algorithm Maximum a posteriori Maximum a posteriori MAP estimation Hidden Markov model References references External links http www.inference.phy.cam.ac.uk mackay itila The on line textbook Information Theory, Inference, and Learning Algorithms , by David J.C. MacKay , discusses the BCJR algorithm in chapter 25. DEFAULTSORT Bcjr Algorithm Category Error detection and correction algorithm stub math stub Wireless stub de BCJR Algorithmus ja BCJR ... more details
Multiple issues wikify January 2011 orphan April 2010 one source March 2010 The Viewing Algorithm is an algorithm in computer graphics that helps in displaying the pictures on the screen by using the graphical data structures in the application data structures. Introduction The viewing algorithm is a procedure, implemented either in software or a hardware processor that traverses the application data structure, generating the picture that is transformed, clipped and passed to refresh the display. For real time graphics the process needs to be repeated continuously at a sufficient rate to maintain the picture on the screen flicker free. When the data structure is modified, the change shows immediately in a fresh picture. Viewing algorithm requires the programmer to device an appropriate data structure, together with one or more viewing algorithm that will produce suitable pictorial representation of the data. The application program is designed to execute the selected algorithm iteratively to maintain the picture on the screen. Drawbacks It is quite difficult and expensive to implement. All the processes of algorithm depend on the ability of system and require high performance displays like LDS 1 , to traverse data structure, transform and clip graphical data found in application data structure and to display it on the screen rapidly enough to avoid flicker. The model stircts the programmer to a simple linked list data structure that must be held entirely in the primary memory. The model allows only a single graphical representation of data structure, i.e. single viewing algorithm. Modification Another data structure is introduced in the process in order to attempt to overcome these drawbacks. This is done by making use of separate Structure Display File to support the refresh ... of application data structure. In this modified model, we apply viewing algorithm to application data structure to get the Structure Display File to which a more constrained algorithm is then applied ... more details
Bat inspired algorithm is a metaheuristic search optimization developed by Xin She Yang in 2010. ref X. S. Yang, A New Metaheuristic Bat Inspired Algorithm, in Nature Inspired Cooperative Strategies for Optimization NISCO 2010 Eds. J. R. Gonzalez et al. , Studies in Computational Intelligence, Springer Berlin, 284, Springer, 65 74 2010 . http arxiv.org abs 1004.4170 ref This bat algorithm is based on the echolocation behaviour of microbats with varying pulse rates of emission and loudness. ref J. D. Altringham, Bats Biology and Behaviour, Oxford University Press, 1996 . ref ref P. Richardson, Bats. Natural History Museum, London, 2008 ref Algorithm Description The idealization of the echolocation of microbats can be summarized as follows Each virtual bat flies randomly with a velocity math v i math at position solution math x i math with a varying frequency or wavelength and loudness math A i math . As it searches and finds its prey, it changes frequency, loudness and pulse emission rate ... algorithm is given by Yang ref Yang, X. S., Nature Inspired Metaheuristic Algoirthms, 2nd Edition ... improvement is the development of an evolving bat algorithm EBA with better efficiency. ref P. W. Tsai, J. S. Pan, B. Y. Liao, M. J. Tsai, V. Istanda, Bat algorithm inspired algorithm for solving ... Multi objective Bat Algorithm MOBA Using a simple weighted sum with random weights, a very effective but yet simple multiobjective bat algorithm MOBA has been developed to solve multiobjective engineering design tasks. ref X. S. Yang, bat algorithm for multi objective optimisation, Int. J. Bio Inspired Computation, Vol. 3, 267 274 2011 . ref Another multiobjective bat algorithm by combining bat algorithm with NSGA II produces very competitive results with good efficiency. ref T. C. Bora, L. S. Coelho ... and bat algorithm has shown a reliable match between prediction and actual data for exergy modelling. ref T. A. Lemma, Use of fuzzy systems and bat algorithm for exergy modelling in a gas turbine ... more details
The term auction algorithm ref name MITmwm applies to several variations of a Optimization mathematics combinatorial optimization algorithm which solves assignment problem s, and network optimization problems with linear and convex nonlinear cost. An auction algorithm has been used in a business setting ... procedure, so the name auction algorithm is related to a sales auction , where multiple bids are compared ... form of the auction algorithm is an iterative method to find the optimal prices and an assignment that maximizes ... accessdate 10 March 2010 year 2006 publisher Birkh user isbn 9780387306629 ref This algorithm ... algorithm has excellent computational complexity, as given in these books, and is reputed ... of the auction algorithm that solves shortest path problem s was introduced by Bertsekas in 1991. ref ... algorithm for finding shortest paths in a directed graph . ref name Bert91 In the single origin single destination case, the auction algorithm maintains a single path starting at the origin ... of a dual function. In the case of multiple origins, the auction algorithm is well suited for parallel computation. ref name Bert91 The algorithm is closely related to auction algorithms for other network flow problems. ref name Bert91 According to computational experiments, the auction algorithm .... ref name Bert91 This is also a parallel auction algorithm for weighted bipartite matching, described by E. Jason Riedy in 2004. ref name BerkPA The Parallel Auction Algorithm for Weighted Bipartite .... ref name DTUauc Experiments clearly show that the auction algorithm is inferior to the state of the art ... with the auction algorithm for the shortest path problem first1 Jesper last1 Larsen first2 ... tekniske.rapporter rapporter 97 07.pdf A note on the practical performance of the auction algorithm for the shortest path 1997 by the first author. ref Although in the auction algorithm, each iteration never decreases the total benefit increases or remains the same , with the alternative Hungarian algorithm ... more details
Multiple issues one source May 2008 refimprove May 2008 orphan May 2008 The Algorithm BSTW is a data compression algorithm, named after its designers, Bentley, Sleator, Tarjan and Wei in 1986. BSTW is a dictionary based algorithm that uses a move to front transform to keep recently seen dictionary entries at the front of the dictionary. Dictionary references are then encoded using any of a number of encoding methods, usually Elias delta coding or Elias gamma coding . References This algorithm was published in the following paper Ryabko, B. Ya. Data compression by means of a book stack , Problems of Information Transmission, 1980, v. 16 4 , pp. 265 269. The original name of this code is book stack . The history of discovery of the book stack or Move to front transform move to front code can be found here Ryabko, B. Ya. Horspool, R. Nigel Cormack, Gordon V. Comments to http dl.acm.org citation.cfm?id 568 A locally adaptive data compression scheme by J. L. Bentley, D. D. Sleator, R. E. Tarjan and V. K. Wei. Comm. ACM 30 1987 , no. 9, 792 794. External links http www.ics.uci.edu dan pubs DC Sec5.html Sec 5.2 Algorithm BSTW Category Lossless compression algorithms algorithm stub ... more details
In computer science , Cannon s algorithm is a distributed algorithm for matrix multiplication for two dimensional mesh es first described in 1969 by Lynn Elliot Cannon . ref Lynn Elliot Cannon, http portal.acm.org citation.cfm?coll GUIDE&dl GUIDE&id 905686 A cellular computer to implement the Kalman Filter Algorithm , Technical report, Ph.D. Thesis, Montana State University, 14 July 1969. ref ref name stanfordpaper http dbpubs.stanford.edu 8090 pub 1994 25 Gupta, H. Sadayappan, P. Communication Efficient Matrix Multiplication on Hypercubes , dbpubs.stanford.edu ref It is especially suitable for computers laid out in an N N mesh. ref name mpgde http www.ipp.mpg.de de for bereiche stellarator Comp sci CompScience csep csep1.phy.ornl.gov la node6.html 4.2 Matrix Multiplication on a Distributed Memory Machine , ipp.mpg.de ref While Cannon s algorithm works well in homogeneous 2D grids, extending it to heterogeneous 2D grids has been proven to be difficult. ref name lyonfr http graal.ens lyon.fr jfpineau research.html Research , graal.ens lyon.fr ref The main advantage of the algorithm is that its storage requirements remain constant and are independent of the number of processors. ref name stanfordpaper See also Systolic array References references External links http www.cs.berkeley.edu demmel cs267 lecture11 lecture11.html Lecture at Berkeley http www.cs.mu.oz.au 498 notes node30.html mu.oz.au Numerical linear algebra DEFAULTSORT Cannon s Algorithm Category Distributed algorithms Category Numerical linear algebra mathapplied stub fr Algorithme de Cannon th ... more details
Merge Swendsen Wang algorithm discuss Talk Swendsen Wang algorithm date March 2009 The Wolff algorithm , named after Ulli Wolff , is an algorithm for Monte Carlo simulation of the Ising model in which an equal spin cluster is formed around one spin. That cluster is then flipped. The Wolff algorithm is an improvement over the Swendsen Wang algorithm because it tends to form bigger clusters. References citation doi 10.1103 PhysRevLett.62.361 title Collective Monte Carlo Updating for Spin Systems year 1989 author Wolff, Ulli journal Physical Review Letters volume 62 pages 361 pmid 10040213 issue 4 bibcode 1989PhRvL..62..361W citation doi 10.1142 S0129183195000150 title Parallel Wolff cluster algorithms year 1995 author1 Bae, S. author2 Ko, S.H. author3 Coddington, P.D. journal International Journal of Modern Physics C volume 6 issue 2 pages 197 bibcode 1995IJMPC...6..197B citation doi 10.1103 PhysRevLett.69.3382 title Monte Carlo simulations Hidden errors from good random number generators year 1992 author1 Ferrenberg, Alan M. author2 Landau, D.P. author3 Wong, Y. Joanna journal Physical Review Letters volume 69 pages 3382 pmid 10046804 issue 23 bibcode 1992PhRvL..69.3382F External links http www.netlib.org utk lsi pcwLSI text node292.html Cluster Algorithms at Netlib Category Monte Carlo methods Category Statistical mechanics physics stub de Wolff Algorithmus ... more details
multiple issues orphan May 2010 unreferenced May 2007 GSP Algorithm Generalized Sequential Pattern algorithm is an algorithm used for sequence mining . The algorithms for solving sequence mining problems are mostly based on the apriori algorithm a priori level wise algorithm. One way to use the level wise paradigm is to first discover all the frequent items in a level wise fashion. It simply means counting the occurrences of all singleton elements in the database. Then, the transaction database transactions are filtered by removing the non frequent items. At the end of this step, each transaction consists of only the frequent elements it originally contained. This modified database becomes an input to the GSP algorithm. This process requires one pass over the whole database . GSP Algorithm makes multiple database passes. In the first pass, all single items 1 sequences are counted. From the frequent items, a set of candidate 2 sequences are formed, and another pass is made to identify their frequency. The frequent 2 sequences are used to generate the candidate 3 sequences, and this process is repeated until no more frequent sequences are found. There are two main steps in the algorithm. Candidate Generation. Given the set of frequent k 1 frequent sequences F k 1 , the candidates for the next pass are generated by joining F k 1 with itself. A pruning phase eliminates any sequence, at least one of whose subsequences is not frequent. Support Counting. Normally, a hash tree &ndash .... Algorithm code F1 the set of frequent 1 sequence k 2, do while F k 1 Null Generate candidate ... Set of all frequent sequences is the union of all Fks End do End do code The above algorithm looks like the Apriori algorithm . One main difference is however the generation of candidate sets. Let us ... algorithm discovers frequent sequences, allowing for time constraints such as maximum gap and minimum ... 380 4 pp. 256 260 page 256 DEFAULTSORT Gsp Algorithm Category Data mining Category Articles with example ... more details
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