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Parallel ArcConsistency for Functional Constraints
"... We present in this paper a parallel execution model of arcconsistency for Constraint Satisfaction Problems (CSP), implemented on a scaleable MIMD distributed memory machine. We have adopted the indexical scheme, an adequate approach to arcconsistency for functional constraints. The CSP is parti ..."
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is partitioned into N partitions, which are executed in parallel on N processors. Each processor applies sequential arcconsistency to its subset of constraints, updating remote domains of variables shared by any other processor. The parallel algorithm we propose is embedded in the constraint solver PCSOS
Optimal Distributed ArcConsistency
 In Proceedings of CP’99
, 1999
"... This paper presents DisAC9, the rst optimal distributed algorithm performing the arcconsistency of a constraint network. Our method is optimal according to the number of message passing operations. ..."
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Cited by 14 (4 self)
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This paper presents DisAC9, the rst optimal distributed algorithm performing the arcconsistency of a constraint network. Our method is optimal according to the number of message passing operations.
Optimal Distributed ArcConsistency
 In Proceedings of CP’99
, 1999
"... This paper presents DisAC9, the rst optimal distributed algorithm performing the arcconsistency of a constraint network. Our method is optimal according to the number of message passing operations. This algorithm can rstly, give speedup over the fastest central arcconsistency algorithms; secon ..."
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This paper presents DisAC9, the rst optimal distributed algorithm performing the arcconsistency of a constraint network. Our method is optimal according to the number of message passing operations. This algorithm can rstly, give speedup over the fastest central arcconsistency algorithms
Parallelisation of ArcConsistency Algorithms
 IN JORNADAS CHILENAS DE COMPUTACIÓN, 2002. VI WORKSHOP ON DISTRIBUTED SYSTEMS AND PARALLELISM, COPIAPÓCHILE
, 2002
"... This work presents the parallelisation of the AC5 arcconsistency algorithm for two dierent parallel architectures. One is a cluster of PCs and the other is a centralised memory machine (CMM). We conducted our experiments using an adapted version of the PCSOS parallel constraint solving system, ..."
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Cited by 2 (2 self)
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This work presents the parallelisation of the AC5 arcconsistency algorithm for two dierent parallel architectures. One is a cluster of PCs and the other is a centralised memory machine (CMM). We conducted our experiments using an adapted version of the PCSOS parallel constraint solving system
Analysis of Distributed ArcConsistency Algorithms
, 1997
"... Consistency techniques can significantly reduce the search space of constraint satisfaction problems (CSP). In particular, arcconsistency algorithms, such as AC3 [7], AC4 [8] and AC6 [2], have been designed. In [9], we presented DisAC4, a coarsegrained parallel algorithm designed for distribut ..."
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Cited by 51 (0 self)
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Consistency techniques can significantly reduce the search space of constraint satisfaction problems (CSP). In particular, arcconsistency algorithms, such as AC3 [7], AC4 [8] and AC6 [2], have been designed. In [9], we presented DisAC4, a coarsegrained parallel algorithm designed
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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of available computers, communicating as appropriate through files, TCP pipes, and sharedmemory FIFOs. The vertices provided by the application developer are quite simple and are usually written as sequential programs with no thread creation or locking. Concurrency arises from Dryad scheduling vertices to run
ArcConsistency Algorithms on a Software DSM Platform
 Colloquium on Implementation of Cronstraint and Logic Programming Systems  CICLOPS 2001, (NMSUCSTR003/2001):103–117
, 2001
"... This work presents the parallelisation of the AC5 arcconsistency algorithm for distributedshared memory platforms. We conducted our experiments using an adapted version of the PCSOS parallel system, over nite domains, running on top of Treadmarks, a software DSM system, on a cluster of 8 PCs c ..."
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Cited by 2 (1 self)
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This work presents the parallelisation of the AC5 arcconsistency algorithm for distributedshared memory platforms. We conducted our experiments using an adapted version of the PCSOS parallel system, over nite domains, running on top of Treadmarks, a software DSM system, on a cluster of 8 PCs
DecisionTheoretic Planning: Structural Assumptions and Computational Leverage
 JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH
, 1999
"... Planning under uncertainty is a central problem in the study of automated sequential decision making, and has been addressed by researchers in many different fields, including AI planning, decision analysis, operations research, control theory and economics. While the assumptions and perspectives ..."
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Cited by 510 (4 self)
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Planning under uncertainty is a central problem in the study of automated sequential decision making, and has been addressed by researchers in many different fields, including AI planning, decision analysis, operations research, control theory and economics. While the assumptions
Estimating the Support of a HighDimensional Distribution
, 1999
"... Suppose you are given some dataset drawn from an underlying probability distribution P and you want to estimate a "simple" subset S of input space such that the probability that a test point drawn from P lies outside of S is bounded by some a priori specified between 0 and 1. We propo ..."
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Cited by 766 (29 self)
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of the weight vector in an associated feature space. The expansion coefficients are found by solving a quadratic programming problem, which we do by carrying out sequential optimization over pairs of input patterns. We also provide a preliminary theoretical analysis of the statistical performance of our
Static Scheduling of Synchronous Data Flow Programs for Digital Signal Processing
 IEEE TRANSACTIONS ON COMPUTERS
, 1987
"... Large grain data flow (LGDF) programming is natural and convenient for describing digital signal processing (DSP) systems, but its runtime overhead is costly in real time or costsensitive applications. In some situations, designers are not willing to squander computing resources for the sake of pro ..."
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Cited by 592 (37 self)
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Large grain data flow (LGDF) programming is natural and convenient for describing digital signal processing (DSP) systems, but its runtime overhead is costly in real time or costsensitive applications. In some situations, designers are not willing to squander computing resources for the sake of programmer convenience. This is particularly true when the target machine is a programmable DSP chip. However, the runtime overhead inherent in most LGDF implementations is not required for most signal processing systems because such systems are mostly synchronous (in the DSP sense). Synchronous data flow (SDF) differs from traditional data flow in that the amount of data produced and consumed by a data flow node is specified a priori for each input and output. This is equivalent to specifying the relative sample rates in signal processing system. This means that the scheduling of SDF nodes need not be done at runtime, but can be done at compile time (statically), so the runtime overhead evaporates. The sample rates can all be different, which is not true of most current datadriven digital signal processing programming methodologies. Synchronous data flow is closely related to computation graphs, a special case of Petri nets. This selfcontained paper develops the theory necessary to statically schedule SDF programs on single or multiple processors. A class of static (compile time) scheduling algorithms is proven valid, and specific algorithms are given for scheduling SDF systems onto single or multiple processors.
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