Search results for "sively"

showing 10 items of 40 documents

Reference set of Mycobacterium tuberculosis clinical strains: A tool for research and product development

2018

TheMycobacterium tuberculosiscomplex (MTBC) causes tuberculosis (TB) in humans and various other mammals. The human-adapted members of the MTBC comprise seven phylogenetic lineages that differ in their geographical distribution. There is growing evidence that this phylogenetic diversity modulates the outcome of TB infection and disease. For decades, TB research and development has focused on the two canonical MTBC reference strains H37Rv and Erdman, both of which belong to Lineage 4. Relying on only a few laboratory-adapted strains can be misleading as study results might not be directly transferrable to clinical settings where patients are infected with a diverse array of strains, includin…

Bacterial DiseasesResearch FacilitiesExtensively Drug-Resistant TuberculosisLineage (evolution)DiseaseAnimal PhylogeneticsMedicine and Health SciencesPhylogenyData Management0303 health sciencesGeographyPhylogenetic treeStrain (biology)QRGenomics3. Good healthActinobacteriaPhylogeneticsPhylogeographyInfectious DiseasesBiogeographyMycobacterium tuberculosis complexMedicineResearch LaboratoriesResearch ArticleComputer and Information SciencesTuberculosisTuberculosiScienceBiologyResearch and Analysis MethodsMycobacterium tuberculosis03 medical and health sciencesGenomic MedicineGeneticsmedicineTuberculosisHumansEvolutionary SystematicsTaxonomy030304 developmental biologyEvolutionary BiologyPopulation BiologyBacteria030306 microbiologyEcology and Environmental SciencesOrganismsBiology and Life SciencesGenetic VariationMycobacterium tuberculosisTropical Diseasesbiology.organism_classificationmedicine.diseaseGenòmicaPhylogenetic diversityEvolutionary biologyEarth SciencesZoologyPopulation Genetics
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CRiSPy-CUDA: Computing Species Richness in 16S rRNA Pyrosequencing Datasets with CUDA

2011

Pyrosequencing technologies are frequently used for sequencing the 16S rRNA marker gene for metagenomic studies of microbial communities. Computing a pairwise genetic distance matrix from the produced reads is an important but highly time consuming task. In this paper, we present a parallelized tool (called CRiSPy) for scalable pairwise genetic distance matrix computation and clustering that is based on the processing pipeline of the popular ESPRIT software package. To achieve high computational efficiency, we have designed massively parallel CUDA algorithms for pairwise k-mer distance and pairwise genetic distance computation. We have also implemented a memory-efficient sparse matrix clust…

CUDADistance matrixComputer scienceMetagenomicsPipeline (computing)Pairwise comparisonParallel computingCluster analysisQuantitative Biology::GenomicsMassively parallelSparse matrix
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Computational Methods for Gene Expression Profiling Using Next-Generation Sequencing (RNA-Seq)

2014

Cancer genome sequencingMassive parallel sequencingSingle cell sequencingComputational biologyBiologyBioinformaticsDeep sequencingExome sequencingDNA sequencingIllumina dye sequencingMassively parallel signature sequencing
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Co-learnability and FIN-identifiability of enumerable classes of total recursive functions

1994

Co-learnability is an inference process where instead of producing the final result, the strategy produces all the natural numbers but one, and the omitted number is an encoding of the correct result. It has been proved in [1] that co-learnability of Goedel numbers is equivalent to EX-identifiability. We consider co-learnability of indices in recursively enumerable (r.e.) numberings. The power of co-learnability depends on the numberings used. Every r.e. class of total recursive functions is co-learnable in some r.e. numbering. FIN-identifiable classes are co-learnable in all r.e. numberings, and classes containing a function being accumulation point are not co-learnable in some r.e. number…

CombinatoricsClass (set theory)TheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESTheoryofComputation_COMPUTATIONBYABSTRACTDEVICESConjectureRecursively enumerable languageLimit pointIdentifiabilityNatural numberFunction (mathematics)NumberingMathematics
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Massively parallel computation of atmospheric neutrino oscillations on CUDA-enabled accelerators

2019

Abstract The computation of neutrino flavor transition amplitudes through inhomogeneous matter is a time-consuming step and thus could benefit from optimization and parallelization. Next to reliable parameter estimation of intrinsic physical quantities such as neutrino masses and mixing angles, these transition amplitudes are important in hypothesis testing of potential extensions of the standard model of elementary particle physics, such as additional neutrino flavors. Hence, fast yet precise implementations are of high importance to research. In the recent past, massively parallel accelerators such as CUDA-enabled GPUs featuring thousands of compute units have been widely adopted due to t…

Computer scienceComputationGeneral Physics and AstronomyMemory bandwidth01 natural sciences010305 fluids & plasmasStandard ModelComputational scienceCUDAHardware and Architecture0103 physical sciencesNeutrino010306 general physicsNeutrino oscillationMassively parallelPhysical quantityComputer Physics Communications
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Live demonstration: multiplexing AER asynchronous channels over LVDS Links with Flow-Control and Clock-Correction for Scalable Neuromorphic Systems

2017

Paper presented at the 2017 IEEE International Symposium on Circuits and Systems (ISCAS), held in Baltimore, MD, USA, on 28-31 May 2017.

Computer scienceSerial communicationGabor filters02 engineering and technologyMultiplexingMultiplexing0202 electrical engineering electronic engineering information engineeringComputerSystemsOrganization_SPECIAL-PURPOSEANDAPPLICATION-BASEDSYSTEMSField-programmable gate arrayComputer Science::Operating SystemsMassively parallelNeuromorphicsReal-time systemsSpiking neural networkQuantitative Biology::Neurons and CognitionArtificial neural networkbusiness.industry020208 electrical & electronic engineeringField programmable gate arraysNeuromorphic engineeringAsynchronous communicationEmbedded systemVoltage controlbusinessComputer hardwareNeural networksHardware_LOGICDESIGN
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Derived sets and inductive inference

1994

The paper deals with using topological concepts in studies of the Gold paradigm of inductive inference. They are — accumulation points, derived sets of order α (α — constructive ordinal) and compactness. Identifiability of a class U of total recursive functions with a bound α on the number of mindchanges implies \(U^{(\alpha + 1)} = \not 0\). This allows to construct counter-examples — recursively enumerable classes of functions showing the proper inclusion between identification types: EXα⊂EXα+1.

Discrete mathematicsClass (set theory)Compact spaceRecursively enumerable languageLimit pointOrder (ring theory)IdentifiabilityInductive reasoningConstructiveMathematics
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Enumerable classes of total recursive functions: Complexity of inductive inference

1994

This paper includes some results on complexity of inductive inference for enumerable classes of total recursive functions, where enumeration is considered in more general meaning than usual recursive enumeration. The complexity is measured as the worst-case mindchange (error) number for the first n functions of the given class. Three generalizations are considered.

Discrete mathematicsClass (set theory)Mathematics::CombinatoricsTheoretical computer scienceRecursively enumerable setRecursive functionsEnumerationInductive reasoningMathematics
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Multi-GPU Accelerated Multi-Spin Monte Carlo Simulations of the 2D Ising Model

2010

A Modern Graphics Processing unit (GPU) is able to perform massively parallel scientific computations at low cost. We extend our implementation of the checkerboard algorithm for the two-dimensional Ising model [T. Preis et al., Journal of Chemical Physics 228 (2009) 4468–4477] in order to overcome the memory limitations of a single GPU which enables us to simulate significantly larger systems. Using multi-spin coding techniques, we are able to accelerate simulations on a single GPU by factors up to 35 compared to an optimized single Central Processor Unit (CPU) core implementation which employs multi-spin coding. By combining the Compute Unified Device Architecture (CUDA) with the Message P…

FOS: Computer and information sciencesComputer scienceMonte Carlo methodGraphics processing unitFOS: Physical sciencesGeneral Physics and AstronomyMathematical Physics (math-ph)Parallel computingGPU clusterComputational Physics (physics.comp-ph)Graphics (cs.GR)Computational scienceCUDAComputer Science - GraphicsHardware and ArchitectureIsing modelCentral processing unitGeneral-purpose computing on graphics processing unitsMassively parallelPhysics - Computational PhysicsMathematical Physics
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LARGE-SCALE SIMULATIONS IN CONDENSED MATTER PHYSICS —THE NEED FOR A TERAFLOP COMPUTER

1992

The introduction of vector processors {“supercomputers” with a performance in the range of 109 floating point operations (1 GFLOP) per second} has had an enormous impact on computational condensed matter physics. The possibility of a substantially enhanced performance by massively parallel processors (“teraflop” machines with 1012 floating point operations per second) will allow satisfactory treatment of a large range of important scientific problems which have to a great extent thus far escaped numerical resolution. The present paper describes only a few examples (out of a long list of interesting research problems!) for which the availability of “teraflops” will allow spectacular progres…

Floating pointCondensed matter physicsComputer scienceScale (chemistry)Monte Carlo methodGeneral Physics and AstronomyStatistical and Nonlinear PhysicsParallel computingLarge rangeFLOPSComputer Science ApplicationsMetallic alloyRange (mathematics)Computational Theory and MathematicsMassively parallelMathematical PhysicsInternational Journal of Modern Physics C
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