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An Efficient Deterministic Parallel Algorithm for Adaptive Multidimensional Numerical Integration on GPUs
"... Recent development in Graphics Processing Units (GPUs) has enabled a new ..."
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Cited by 2 (1 self)
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Recent development in Graphics Processing Units (GPUs) has enabled a new
CommunicationEfficient Deterministic Parallel Algorithms for Planar Point Location and 2d Voronoi Diagram
, 1998
"... In this paper we describe deterministic parallel algorithms for planar point location and for building the Voronoi Diagram of n coplanar points. These algorithms are designed for BSPlike models of computation, where p processors, with O( n p ) AE O(1) local memory each, communicate through some ar ..."
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Cited by 3 (1 self)
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In this paper we describe deterministic parallel algorithms for planar point location and for building the Voronoi Diagram of n coplanar points. These algorithms are designed for BSPlike models of computation, where p processors, with O( n p ) AE O(1) local memory each, communicate through some
A Note on CommunicationEfficient Deterministic Parallel Algorithms for Planar Point Location and 2d Voronoï Diagram
"... In this note we describe deterministic parallel algorithms for planar point location and for building the Voronoï Diagram of n coplanar points. These algorithms are designed for BSP/CGMlike models of computation, where p processors, with O ( n) O(1) local memory p each, communicate through some a ..."
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Cited by 1 (0 self)
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In this note we describe deterministic parallel algorithms for planar point location and for building the Voronoï Diagram of n coplanar points. These algorithms are designed for BSP/CGMlike models of computation, where p processors, with O ( n) O(1) local memory p each, communicate through some
A Note on CommunicationEfficient Deterministic Parallel Algorithms for Planar Point Location and 2d Voronoi " Diagram\Lambda
"... Abstract In this note we describe deterministic parallel algorithms for planar point location and for building the Voronoi " Diagram of n coplanar points. These algorithms are designed for BSP/CGMlike models of computation, where p processors, with O ( np) AE O(1) local memory each, commu ..."
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Abstract In this note we describe deterministic parallel algorithms for planar point location and for building the Voronoi " Diagram of n coplanar points. These algorithms are designed for BSP/CGMlike models of computation, where p processors, with O ( np) AE O(1) local memory each
Cilk: An Efficient Multithreaded Runtime System
 JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING
, 1995
"... Cilk (pronounced "silk") is a Cbased runtime system for multithreaded parallel programming. In this paper, we document the efficiency of the Cilk workstealing scheduler, both empirically and analytically. We show that on real and synthetic applications, the "work" and "cri ..."
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Cited by 750 (40 self)
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Cilk (pronounced "silk") is a Cbased runtime system for multithreaded parallel programming. In this paper, we document the efficiency of the Cilk workstealing scheduler, both empirically and analytically. We show that on real and synthetic applications, the "work" and "
Parallel Numerical Linear Algebra
, 1993
"... We survey general techniques and open problems in numerical linear algebra on parallel architectures. We first discuss basic principles of parallel processing, describing the costs of basic operations on parallel machines, including general principles for constructing efficient algorithms. We illust ..."
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Cited by 766 (23 self)
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We survey general techniques and open problems in numerical linear algebra on parallel architectures. We first discuss basic principles of parallel processing, describing the costs of basic operations on parallel machines, including general principles for constructing efficient algorithms. We
Dryad: Distributed DataParallel Programs from Sequential Building Blocks
 In EuroSys
, 2007
"... Dryad is a generalpurpose distributed execution engine for coarsegrain dataparallel applications. A Dryad application combines computational “vertices ” with communication “channels ” to form a dataflow graph. Dryad runs the application by executing the vertices of this graph on a set of availa ..."
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Cited by 730 (27 self)
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Dryad is a generalpurpose distributed execution engine for coarsegrain dataparallel applications. A Dryad application combines computational “vertices ” with communication “channels ” to form a dataflow graph. Dryad runs the application by executing the vertices of this graph on a set
Stochastic Inversion Transduction Grammars and Bilingual Parsing of Parallel Corpora
, 1997
"... ..."
Fast Parallel Algorithms for ShortRange Molecular Dynamics
 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 interatomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dyn ..."
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Cited by 622 (6 self)
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dynamics models which can be difficult to parallelize efficiently  those with shortrange forces where the neighbors of each atom change rapidly. They can be implemented on any distributedmemory parallel machine which allows for messagepassing of data between independently executing processors
Implementing data cubes efficiently
 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 ..."
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Cited by 545 (1 self)
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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 sales. The values of many of these cells are dependent on the values of other cells in the data cube..A common and powerful query optimization technique is to materialize some or all of these cells rather than compute them from raw data each time. Commercial systems differ mainly in their approach 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 to materialize. The greedy algorithm performs within a small constant factor of optimal under a variety of models. We then consider the most common case of the hypercube lattice and examine the choice of materialized views for hypercubes in detail, giving some good tradeoffs between the space used and the average time to answer a query. 1
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