Search results for "Cluster computing"

showing 10 items of 120 documents

MetaCache-GPU: Ultra-Fast Metagenomic Classification

2021

The cost of DNA sequencing has dropped exponentially over the past decade, making genomic data accessible to a growing number of scientists. In bioinformatics, localization of short DNA sequences (reads) within large genomic sequences is commonly facilitated by constructing index data structures which allow for efficient querying of substrings. Recent metagenomic classification pipelines annotate reads with taxonomic labels by analyzing their $k$-mer histograms with respect to a reference genome database. CPU-based index construction is often performed in a preprocessing phase due to the relatively high cost of building irregular data structures such as hash maps. However, the rapidly growi…

Genomics (q-bio.GN)FOS: Computer and information sciencesSource codeComputer sciencemedia_common.quotation_subjectHash functionContext (language use)MinHashcomputer.software_genreData structureHash tableComputer Science - Distributed Parallel and Cluster ComputingFOS: Biological sciencesPreprocessorQuantitative Biology - GenomicsDistributed Parallel and Cluster Computing (cs.DC)Data miningcomputermedia_commonReference genome50th International Conference on Parallel Processing
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Dendrochemical assessment of mercury releases from a pond and dredged-sediment landfill impacted by a chlor-alkali plant.

2016

International audience; Although current Hg emissions from industrial activities may be accurately monitored, evidence of past releases to the atmosphere must rely on one or more environmental proxies. We used Hg concentrations in tree cores collected from poplars and willows to investigate the historical changes of Hg emissions from a dredged sediment landfill and compared them to a nearby control location. Our results demonstrated the potential value of using dendrochemistry to record historical Hg emissions from past industrial activities.

Geologic Sediments010504 meteorology & atmospheric scienceschemistry.chemical_elementIndustrial Waste[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]010501 environmental sciencesGeologic SedimentsAlkalies01 natural sciencesBiochemistryIndustrial waste[ SDV.EE ] Life Sciences [q-bio]/Ecology environmentTrees[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]Waste Disposal Facilityddc:550Salicaceous speciesPondsComputingMilieux_MISCELLANEOUS0105 earth and related environmental sciencesGeneral Environmental Science[SDV.EE]Life Sciences [q-bio]/Ecology environmentChlor-alkali plantEcologyTree ringsSalixMercury[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationMercury (element)Waste Disposal FacilitiesPopuluschemistry13. Climate action[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]Environmental chemistryEnvironmental scienceDendrochemistry[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET]Environmental Pollutants[INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]Environmental research
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Advances in the enumeration of foldable self-avoiding walks

2020

<font color="#336633"&gtSelf-avoiding walks (SAWs) have been studied for a long time due to their intrinsic importance and the many application fields in which they operate. A new subset of SAWs, called foldable SAWs, has recently been discovered when investigating two different SAW manipulations embedded within existing protein structure prediction (PSP) software. Since then, several attempts have been made to find out more about these walks, including counting them. However, calculating the number of foldable SAWs appeared as a tough work, and current supercomputers fail to count foldable SAWs of length exceeding ≈ 30 steps. In this article, we present new progress in this enumeration, bo…

Hexagonal crystal systemComputer sciencebusiness.industry[INFO.INFO-SE] Computer Science [cs]/Software Engineering [cs.SE][INFO.INFO-IU] Computer Science [cs]/Ubiquitous ComputingUpper and lower boundsParallel genetic algorithmComputational MathematicsSoftwareComputational Theory and MathematicsHardware and ArchitectureModeling and Simulation[INFO.INFO-ET] Computer Science [cs]/Emerging Technologies [cs.ET]Genetic algorithm[INFO.INFO-DC] Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]Enumeration[INFO.INFO-MA] Computer Science [cs]/Multiagent Systems [cs.MA][INFO.INFO-MO] Computer Science [cs]/Modeling and SimulationbusinessAlgorithmSoftware[INFO.INFO-CR] Computer Science [cs]/Cryptography and Security [cs.CR]International Journal of Computational Science and Engineering
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An Efficient Algorithm for Helly Property Recognition in a Linear Hypergraph

2001

International audience; In this article we characterize bipartite graphs whose associated neighborhood hypergraphs have the Helly property. We examine incidence graphs both hypergraphs and linear hypergraphs and we give a polynomial algorithm to recognize if a linear hypergraph has the Helly property.

HypergraphProperty (philosophy)General Computer Science[ INFO.INFO-NI ] Computer Science [cs]/Networking and Internet Architecture [cs.NI]0102 computer and information sciences02 engineering and technologyComputer Science::Computational Geometry01 natural sciencesPolynomial algorithmTheoretical Computer ScienceCombinatorics[INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI][ INFO.INFO-DC ] Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]Computer Science::Discrete Mathematics[ INFO.INFO-TI ] Computer Science [cs]/Image Processing0202 electrical engineering electronic engineering information engineeringMathematics::Metric GeometryComputingMilieux_MISCELLANEOUSMathematicsIncidence (geometry)Discrete mathematicsMathematics::CombinatoricsEfficient algorithm16. Peace & justice010201 computation theory & mathematics[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]Bipartite graph020201 artificial intelligence & image processing[INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]Computer Science(all)Electronic Notes in Theoretical Computer Science
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Numerical simulation of unsteady MHD flows and applications

2009

International audience; We present a robust numerical method for solving the compressible Ideal Magneto-Hydrodynamic equations. It is based on the Residual Distribution (RD) algorithms already successfully tested in many problems. We adapted the scheme to the multi-dimensional unsteady MHD model. The constraint ∇ · B = 0 is enforced by the use a Generalized Lagrange Multiplier (GLM) technique. First, we present this complete system and the keys to get its eigensystem, as we may need it in the algorithm. Next, we introduce the numerical scheme built in order to get a compressible, unsteady and implicit solver which has good shock-capturing properties and is second-order accurate at the conve…

Ideal (set theory)Computer simulationComputer scienceNumerical analysisGeneral Physics and AstronomySolver01 natural sciences010305 fluids & plasmasConstraint (information theory)symbols.namesakeLagrange multiplier0103 physical sciencesCompressibilitysymbols[INFO.INFO-DC] Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]Applied mathematicsElectrical and Electronic EngineeringMagnetohydrodynamics[INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]010306 general physics
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"Table 8" of "Inclusive production of neutral vector mesons in hadronic Z decays"

1995

Average multiplicity per hadronic event. Extrapolation to the full X range.

InclusiveE+ E- --&gt; PHI XHigh Energy Physics::LatticeE+ E- ScatteringHigh Energy Physics::ExperimentComputer Science::Symbolic Computation91.2Nuclear ExperimentComputer Science::Distributed Parallel and Cluster ComputingMULT
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"Table 2" of "Inclusive production of neutral vector mesons in hadronic Z decays"

1995

Average multiplicity per hadronic event. Extrapolation to the full X range.

InclusiveHigh Energy Physics::LatticeE+ E- ScatteringHigh Energy Physics::ExperimentComputer Science::Symbolic Computation91.2Nuclear ExperimentE+ E- --&gt; RHO0 XComputer Science::Distributed Parallel and Cluster ComputingMULT
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"Table 1" of "Production of charged pions, kaons and protons at large transverse momenta in pp and Pb-Pb collisions at sqrt(sNN) = 2.76 TeV"

2014

Invariant yields of identified pions in central and peripheral Pb-Pb collisions, together with the unscaled pp reference yields.

InclusiveProton-Proton Scattering2760.0Nuclear TheoryPB PB --&gt; PI+ XP P --&gt; PI+ XSingle Differential DistributionNuclear ExperimentPB PB --&gt; PI- XP P --&gt; PI- XTransverse Momentum DependenceComputer Science::Distributed Parallel and Cluster ComputingDN/DPT
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"Table 24" of "Studies of quantum chromodynamics with the ALEPH detector"

1997

Unfolded values of the the mean multiplicity and dispersion of the multiplicity distribution integrated over the full rapidity region.

InclusiveQuantitative Biology::BiomoleculesDISPERSIONE+ E- --&gt; Z0E+ E- ScatteringExclusiveComputer Science::Symbolic ComputationE+ E- --&gt; CHARGED X91.2Computer Science::Distributed Parallel and Cluster ComputingMULT
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"Table 6" of "Inclusive production of neutral vector mesons in hadronic Z decays"

1995

Average multiplicity per hadronic event. Extrapolation to the full X range.

InclusiveStrange productionHigh Energy Physics::LatticeE+ E- --&gt; K*(892)0 XE+ E- ScatteringHigh Energy Physics::ExperimentComputer Science::Symbolic Computation91.2Nuclear ExperimentComputer Science::Distributed Parallel and Cluster ComputingMULT
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