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An Efficient Data Parallel Algorithm For 2-D Convolutions

by Sandra Goles Dykes , 1994
"... ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
Abstract not found

Dryad: Distributed Data-Parallel Programs from Sequential Building Blocks

by Michael Isard, Mihai Budiu, Yuan Yu, Andrew Birrell, Dennis Fetterly - In EuroSys , 2007
"... Dryad is a general-purpose distributed execution engine for coarse-grain data-parallel applications. A Dryad applica-tion combines computational “vertices ” with communica-tion “channels ” to form a dataflow graph. Dryad runs the application by executing the vertices of this graph on a set of availa ..."
Abstract - Cited by 762 (27 self) - Add to MetaCart
Dryad is a general-purpose distributed execution engine for coarse-grain data-parallel applications. A Dryad applica-tion combines computational “vertices ” with communica-tion “channels ” to form a dataflow graph. Dryad runs the application by executing the vertices of this graph on a set

Efficient Variants of the ICP Algorithm

by Szymon Rusinkiewicz, Marc Levoy - INTERNATIONAL CONFERENCE ON 3-D DIGITAL IMAGING AND MODELING , 2001
"... The ICP (Iterative Closest Point) algorithm is widely used for geometric alignment of three-dimensional models when an initial estimate of the relative pose is known. Many variants of ICP have been proposed, affecting all phases of the algorithm from the selection and matching of points to the minim ..."
Abstract - Cited by 718 (5 self) - Add to MetaCart
The ICP (Iterative Closest Point) algorithm is widely used for geometric alignment of three-dimensional models when an initial estimate of the relative pose is known. Many variants of ICP have been proposed, affecting all phases of the algorithm from the selection and matching of points

An Efficient Context-Free Parsing Algorithm

by Jay Earley , 1970
"... A parsing algorithm which seems to be the most efficient general context-free algorithm known is described. It is similar to both Knuth's LR(k) algorithm and the familiar top-down algorithm. It has a time bound proportional to n 3 (where n is the length of the string being parsed) in general; i ..."
Abstract - Cited by 798 (0 self) - Add to MetaCart
A parsing algorithm which seems to be the most efficient general context-free algorithm known is described. It is similar to both Knuth's LR(k) algorithm and the familiar top-down algorithm. It has a time bound proportional to n 3 (where n is the length of the string being parsed) in general

An Efficient Boosting Algorithm for Combining Preferences

by Raj Dharmarajan Iyer , Jr. , 1999
"... The problem of combining preferences arises in several applications, such as combining the results of different search engines. This work describes an efficient algorithm for combining multiple preferences. We first give a formal framework for the problem. We then describe and analyze a new boosting ..."
Abstract - Cited by 727 (18 self) - Add to MetaCart
The problem of combining preferences arises in several applications, such as combining the results of different search engines. This work describes an efficient algorithm for combining multiple preferences. We first give a formal framework for the problem. We then describe and analyze a new

Fast Parallel Algorithms for Short-Range Molecular Dynamics

by Steve Plimpton - JOURNAL OF COMPUTATIONAL PHYSICS , 1995
"... Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dyn ..."
Abstract - Cited by 653 (7 self) - Add to MetaCart
dynamics models which can be difficult to parallelize efficiently -- those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed--memory parallel machine which allows for message--passing of data between independently executing processors

CURE: An Efficient Clustering Algorithm for Large Data sets

by Sudipto Guha, Rajeev Rastogi, Kyuseok Shim - Published in the Proceedings of the ACM SIGMOD Conference , 1998
"... Clustering, in data mining, is useful for discovering groups and identifying interesting distributions in the underlying data. Traditional clustering algorithms either favor clusters with spherical shapes and similar sizes, or are very fragile in the presence of outliers. We propose a new clustering ..."
Abstract - Cited by 722 (5 self) - Add to MetaCart
Clustering, in data mining, is useful for discovering groups and identifying interesting distributions in the underlying data. Traditional clustering algorithms either favor clusters with spherical shapes and similar sizes, or are very fragile in the presence of outliers. We propose a new

Theoretical improvements in algorithmic efficiency for network flow problems

by Jack Edmonds, Richard M. Karp - , 1972
"... This paper presents new algorithms for the maximum flow problem, the Hitchcock transportation problem, and the general minimum-cost flow problem. Upper bounds on ... the numbers of steps in these algorithms are derived, and are shown to compale favorably with upper bounds on the numbers of steps req ..."
Abstract - Cited by 560 (0 self) - Add to MetaCart
This paper presents new algorithms for the maximum flow problem, the Hitchcock transportation problem, and the general minimum-cost flow problem. Upper bounds on ... the numbers of steps in these algorithms are derived, and are shown to compale favorably with upper bounds on the numbers of steps

An Algorithm for Tracking Multiple Targets

by Donald B. Reid - IEEE Transactions on Automatic Control , 1979
"... Abstract—An algorithm for tracking multiple targets In a cluttered algorithms. Clustering is the process of dividing the entire environment Is developed. The algorithm Is capable of Initiating tracks, set of targets and measurements into independent groups accounting for false or m[~clngreports, and ..."
Abstract - Cited by 596 (0 self) - Add to MetaCart
target, or that the measurement Is false. nally, it is desirable for an algorithm to be recursive so Target states are estimated from each such da*a-as.soclatloo hypothesis that all the previous data do not have to be reprocessed using a 1C~InlQnfilter. As mere measurements are received, the probabill

Implementing data cubes efficiently

by Venky Harinarayan, Anand Rajaraman, Jeffrey D. Ulman - In SIGMOD , 1996
"... Decision support applications involve complex queries on very large databases. Since response times should be small, query optimization is critical. Users typically view the data as multidimensional data cubes. Each cell of the data cube is a view consisting of an aggregation of interest, like total ..."
Abstract - Cited by 548 (1 self) - Add to MetaCart
to materializing the data cube. In this paper, we investigate the issue of which cells (views) to materialize when it is too expensive to materialize all views. A lattice framework is used to express dependencies among views. We present greedy algorithms that work off this lattice and determine a good set of views
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