Search results for "Hypercube"

showing 10 items of 21 documents

Strong chromatic index of products of graphs

2007

Graphs and Algorithms

General Computer ScienceCritical graphKronecker product[INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM]strong productinduced matchingTheoretical Computer ScienceCombinatoricssymbols.namesakeComputer Science::Discrete MathematicsCartesian productDiscrete Mathematics and CombinatoricsChromatic scaleMathematicsDiscrete mathematicsKronecker productMathematics::Combinatoricslcsh:Mathematics[ INFO.INFO-DM ] Computer Science [cs]/Discrete Mathematics [cs.DM]Cartesian productlcsh:QA1-939Graph[INFO.INFO-DM] Computer Science [cs]/Discrete Mathematics [cs.DM]Edge coloringMSC 05C15strong product.symbolsHypercubeStrong edge colouringMathematicsofComputing_DISCRETEMATHEMATICS
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Quantum search of spatial regions

2003

Can Grover's algorithm speed up search of a physical region - for example a 2-D grid of size sqrt(n) by sqrt(n)? The problem is that sqrt(n) time seems to be needed for each query, just to move amplitude across the grid. Here we show that this problem can be surmounted, refuting a claim to the contrary by Benioff. In particular, we show how to search a d-dimensional hypercube in time O(sqrt n) for d at least 3, or O((sqrt n)(log n)^(3/2)) for d=2. More generally, we introduce a model of quantum query complexity on graphs, motivated by fundamental physical limits on information storage, particularly the holographic principle from black hole thermodynamics. Our results in this model include a…

Holographic principleDiscrete mathematicsQuantum PhysicsComputational complexity theoryFOS: Physical sciencesComputer Science::Software EngineeringGraph theoryGeneral Relativity and Quantum Cosmology (gr-qc)Unitary matrixUpper and lower boundsGeneral Relativity and Quantum CosmologyCombinatoricsHypercubeQuantum Physics (quant-ph)Black hole thermodynamicsQuantum computerMathematics44th Annual IEEE Symposium on Foundations of Computer Science, 2003. Proceedings.
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SimuRed: A flit-level event-driven simulator for multicomputer network performance evaluation

2009

The interconnection network is one of the most important multicomputer components, since it has a great impact on global system performance. Many models and simulators have been proposed to evaluate network performance. This paper presents SimuRed, an event-driven flit-level, cycle-accurate simulator to evaluate different orthogonal network configurations. The core of the simulator has been designed to be expandable and portable to different situations. Some of the advantages of this simulator over other similar tools are its visual interface, its fast execution and its simplicity. Moreover, it is multiplatform and its source code versions (C++ and Java) are freely available under GNU open-…

InterconnectionSource codeGeneral Computer ScienceComputer architecture simulatorJavaComputer scienceEvent (computing)business.industrymedia_common.quotation_subjectControl and Systems EngineeringEmbedded systemNetwork performancePolygon meshHypercubeElectrical and Electronic EngineeringbusinesscomputerSimulationmedia_commoncomputer.programming_languageComputers & Electrical Engineering
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Parallel Simulated Annealing: Getting Super Linear Speedups

2005

The study described in this paper tries to improve and combine different approaches that are able to speed up applications of the Simulated Annealing model. It investigates separately two main aspects concerning the degree of parallelism an implementation can egectively exploit at the initial andfinal periods of an execution. As for case studies, it deals with two implementations: the Job shop Scheduling problem and the poryblio selection problem. The paper reports the results of a large number of experiments, carried out by means of a transputer network and a hypercube system. They give useful suggestions about selecting the most suitable values of the intervention parameters to achieve su…

Mathematical optimizationSpeedupComputational complexity theoryJob shop schedulingParallel processing (DSP implementation)Computer scienceSimulated annealingDegree of parallelismFlow shop schedulingParallel computingHypercubeProceedings. Second Euromicro Workshop on Parallel and Distributed Processing
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A recurrence-free variant of strassen’s algorithm on hypercube

1995

In this paper a non-recursive Strassen’s matrix multiplication algorithm is presented. This new algorithm is suitable to run on parallel environments. Two computational schemes have been worked out exploiting different parallel approaches on hypercube architecture. A comparative analysis is reported. The experiments have been carried out on an nCUBE-2 supercomputer, housed at CNUCE in Pisa, supporting the Express parallel operating system. © 1995, Taylor & Francis Group, LLC. All rights reserved.

Matrix multiplicationGeneral Computer ScienceComputer scienceExpress operating systemComputer Science (all)Parallel computingStrassen’s algorithmSupercomputerMatrix multiplicationStrassen algorithmHypercube architectureHypercubeAlgorithmHypercube architecture
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The Lineshape of Inelastic Neutron Scattering in Relaxor Ferroelectrics

2005

We show that a microscopic reason for the steep drop of the optical phonon branch into an acoustic one (the so-called waterfall effect) in relaxor ferroelectrics may be the coupling of phonons with defects and impurities of different kinds, which is always present in relaxors. Namely, we do not specify the type of impurities but rather represent them as an ensemble of so-called two-level systems (TLS). This approach makes it possible to trace the evolution of the “waterfall” with temperature and the TLS concentration. To facilitate the planning of experiments on inelastic neutron scattering, we present a modification of the so-called Latin hypercube sampling method, which, based on some sig…

PhysicsCondensed Matter::Materials ScienceLatin hypercube sampling methodSolid-state physicsCondensed matter physicsImpurityPhononDrop (liquid)Condensed Matter PhysicsInelastic neutron scatteringElectronic Optical and Magnetic MaterialsPhysics of the Solid State
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Surface tension and interfacial fluctuations in d-dimensional Ising model

2005

The surface tension of rough interfaces between coexisting phases in 2D and 3D Ising models are discussed in view of the known results and some original calculations presented in this paper. The results are summarised in a formula, which allows to interpolate the corrections to finite-size scaling between two and three dimensions. The physical meaning of an analytic continuation to noninteger values of the spatial dimensionality d is discussed. Lattices and interfaces with properly defined fractal dimensions should fulfil certain requirements to possibly have properties of an analytic continuation from d-dimensional hypercubes. Here 2 appears as the marginal value of d below which the (d-1)…

PhysicsStatistical Mechanics (cond-mat.stat-mech)Analytic continuationFOS: Physical sciencesGeneral Physics and AstronomyStatistical and Nonlinear PhysicsFractal dimensionComputer Science ApplicationsSurface tensionComputational Theory and MathematicsIsing modelHypercubeStatistical physicsScalingCritical exponentMathematical PhysicsCondensed Matter - Statistical MechanicsCurse of dimensionality
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Radio k-Labelings for Cartesian Products of Graphs

2005

International audience; Frequency planning consists in allocating frequencies to the transmitters of a cellular network so as to ensure that no pair of transmitters interfere. We study the problem of reducing interference by modeling this by a radio k-labeling problem on graphs: For a graph G and an integer k ≥ 1, a radio k-labeling of G is an assignment f of non negative integers to the vertices of G such that |f(x)−f(y)| ≥ k+1−dG(x,y), for any two vertices x and y, where dG(x,y) is the distance between x and y in G. The radio k-chromatic number is the minimum of max{f(x)−f(y):x,y ∈ V(G)} over all radio k-labelings f of G. In this paper we present the radio k-labeling for the Cartesian pro…

Square tilingGraph labelingradio k-labelingradio channel assignmentAntipodal point0102 computer and information sciences[INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM]Span (engineering)01 natural sciencesUpper and lower boundsradio numberCombinatoricssymbols.namesakeIntegerCartesian productDiscrete Mathematics and CombinatoricsChromatic scale0101 mathematicsantipodal numberMathematicsDiscrete mathematicsApplied Mathematics010102 general mathematicsGraph theory[ INFO.INFO-DM ] Computer Science [cs]/Discrete Mathematics [cs.DM]Cartesian productGraph theory[INFO.INFO-DM] Computer Science [cs]/Discrete Mathematics [cs.DM]010201 computation theory & mathematicsCellular networksymbolsHypercubeMSC 05C15 05C78Graph product
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Latin hypercube sampling with inequality constraints

2010

International audience; In some studies requiring predictive and CPU-time consuming numerical models, the sampling design of the model input variables has to be chosen with caution. For this purpose, Latin hypercube sampling has a long history and has shown its robustness capabilities. In this paper we propose and discuss a new algorithm to build a Latin hypercube sample (LHS) taking into account inequality constraints between the sampled variables. This technique, called constrained Latin hypercube sampling (cLHS), consists in doing permutations on an initial LHS to honor the desired monotonic constraints. The relevance of this approach is shown on a real example concerning the numerical w…

Statistics and ProbabilityFOS: Computer and information sciencesEconomics and EconometricsMathematical optimizationDesign of Experiments020209 energyMonotonic functionSample (statistics)Mathematics - Statistics Theory02 engineering and technologyStatistics Theory (math.ST)01 natural sciencesStatistics - Computation010104 statistics & probabilityRobustness (computer science)[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]Sampling design0202 electrical engineering electronic engineering information engineeringFOS: Mathematics[ MATH.MATH-ST ] Mathematics [math]/Statistics [math.ST]0101 mathematicsDependenceUncertainty analysisLatin hypercube samplingComputation (stat.CO)MathematicsApplied MathematicsComputer experimentFunction (mathematics)[STAT.TH]Statistics [stat]/Statistics Theory [stat.TH]Computer experiment[ STAT.TH ] Statistics [stat]/Statistics Theory [stat.TH]Latin hypercube samplingModeling and SimulationUncertainty analysisSocial Sciences (miscellaneous)Analysis
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Kolmogorov Superposition Theorem and Its Application to Multivariate Function Decompositions and Image Representation

2008

International audience; In this paper, we present the problem of multivariate function decompositions into sums and compositions of monovariate functions. We recall that such a decomposition exists in the Kolmogorov's superposition theorem, and we present two of the most recent constructive algorithms of these monovariate functions. We first present the algorithm proposed by Sprecher, then the algorithm proposed by Igelnik, and we present several results of decomposition for gray level images. Our goal is to adapt and apply the superposition theorem to image processing, i.e. to decompose an image into simpler functions using Kolmogorov superpositions. We synthetise our observations, before …

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingImage processing[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technologySuperposition theorem01 natural sciences[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[ INFO.INFO-TI ] Computer Science [cs]/Image ProcessingComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATION0202 electrical engineering electronic engineering information engineeringApplied mathematics0101 mathematics[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingMathematicsDiscrete mathematicsSignal processingArtificial neural network010102 general mathematicsApproximation algorithmSpline (mathematics)[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV]Kolmogorov structure function[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]020201 artificial intelligence & image processingHypercube[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing2008 IEEE International Conference on Signal Image Technology and Internet Based Systems
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