883 resultados para Cluster Computer


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Increased accessibility to high-performance computing resources has created a demand for user support through performance evaluation tools like the iSPD (iconic Simulator for Parallel and Distributed systems), a simulator based on iconic modelling for distributed environments such as computer grids. It was developed to make it easier for general users to create their grid models, including allocation and scheduling algorithms. This paper describes how schedulers are managed by iSPD and how users can easily adopt the scheduling policy that improves the system being simulated. A thorough description of iSPD is given, detailing its scheduler manager. Some comparisons between iSPD and Simgrid simulations, including runs of the simulated environment in a real cluster, are also presented. © 2012 IEEE.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Server responsiveness and scalability are more important than ever in today’s client/server dominated network environments. Recently, researchers have begun to consider cluster-based computers using commodity hardware as an alternative to expensive specialized hardware for building scalable Web servers. In this paper, we present performance results comparing two cluster-based Web servers based on different server infrastructures: MAC-based dispatching (LSMAC) and IP-based dispatching (LSNAT). Both cluster-based server systems were implemented as application-space programs running on commodity hardware. We point out the advantages and disadvantages of both systems. We also identify when servers should be clustered and when clustering will not improve performance.

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Part I : A zinc finger gene Tzf1 was cloned in the earlier work of the lab by screening a ë-DASH2 cDNA expression library with an anti-Rat SC antibody. A ë-DASH2 genomic DNA library and cosmid lawrist 4 genomic DNA library were screened with the cDNA fragment of Tzf1 to determine the genomic organization of Tzf1. Another putative zinc finger gene Tzf2 was found about 700 bp upstream of Tzf1.RACE experiment was carried out for both genes to establish the whole length cDNA. The cDNA sequences of Tzf and Tzf2 were used to search the Flybase (Version Nov, 2000). They correspond to two genes found in the Flybase, CG4413 and CG4936. The CG4413 transcript seems to be a splicing variant of Tzf transcripts. Another two zinc finger genes Tzf3 and Tzf4 were discovered in silico. They are located 300 bp away from Tzf and Tzf2, and a non-tandem cluster was formed by the four genes. All four genes encode proteins with a very similar modular structure, since they all have five C2H2 type zinc fingers at their c-terminal ends. This is the most compact zinc finger protein gene cluster found in Drosophila melanogaster.Part II: 34,056 bp insert of the cosmid 19G11

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Coupled-cluster theory provides one of the most successful concepts in electronic-structure theory. This work covers the parallelization of coupled-cluster energies, gradients, and second derivatives and its application to selected large-scale chemical problems, beside the more practical aspects such as the publication and support of the quantum-chemistry package ACES II MAB and the design and development of a computational environment optimized for coupled-cluster calculations. The main objective of this thesis was to extend the range of applicability of coupled-cluster models to larger molecular systems and their properties and therefore to bring large-scale coupled-cluster calculations into day-to-day routine of computational chemistry. A straightforward strategy for the parallelization of CCSD and CCSD(T) energies, gradients, and second derivatives has been outlined and implemented for closed-shell and open-shell references. Starting from the highly efficient serial implementation of the ACES II MAB computer code an adaptation for affordable workstation clusters has been obtained by parallelizing the most time-consuming steps of the algorithms. Benchmark calculations for systems with up to 1300 basis functions and the presented applications show that the resulting algorithm for energies, gradients and second derivatives at the CCSD and CCSD(T) level of theory exhibits good scaling with the number of processors and substantially extends the range of applicability. Within the framework of the ’High accuracy Extrapolated Ab initio Thermochemistry’ (HEAT) protocols effects of increased basis-set size and higher excitations in the coupled- cluster expansion were investigated. The HEAT scheme was generalized for molecules containing second-row atoms in the case of vinyl chloride. This allowed the different experimental reported values to be discriminated. In the case of the benzene molecule it was shown that even for molecules of this size chemical accuracy can be achieved. Near-quantitative agreement with experiment (about 2 ppm deviation) for the prediction of fluorine-19 nuclear magnetic shielding constants can be achieved by employing the CCSD(T) model together with large basis sets at accurate equilibrium geometries if vibrational averaging and temperature corrections via second-order vibrational perturbation theory are considered. Applying a very similar level of theory for the calculation of the carbon-13 NMR chemical shifts of benzene resulted in quantitative agreement with experimental gas-phase data. The NMR chemical shift study for the bridgehead 1-adamantyl cation at the CCSD(T) level resolved earlier discrepancies of lower-level theoretical treatment. The equilibrium structure of diacetylene has been determined based on the combination of experimental rotational constants of thirteen isotopic species and zero-point vibrational corrections calculated at various quantum-chemical levels. These empirical equilibrium structures agree to within 0.1 pm irrespective of the theoretical level employed. High-level quantum-chemical calculations on the hyperfine structure parameters of the cyanopolyynes were found to be in excellent agreement with experiment. Finally, the theoretically most accurate determination of the molecular equilibrium structure of ferrocene to date is presented.

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CIGS-Dünnschichtsolarzellen verbinden hohe Effizienz mit niedrigen Kosten und sind damit eine aussichtsreiche Photovoltaik-Technologie. Das Verständnis des Absorbermaterials CIGS ist allerdings noch lückenhaft und benötigt weitere Forschung. In dieser Dissertation werden Computersimulationen vorgestellt, die erheblich zum besseren Verständnis von CIGS beitragen. Es wurden die beiden Systeme Cu(In,Ga)Se2 und (Cu,In,Vac)Se betrachtet. Die Gesamtenergie der Systeme wurde in Clusterentwicklungen ausgedrückt, die auf der Basis von ab initio Dichtefunktionalrechnungen erstellt wurden. Damit war es möglich Monte Carlo (MC)-Simulationen durchzuführen. Kanonische MC-Simulationen von Cu(In,Ga)Se2 zeigen das temperaturabhängige Verhalten der In-Ga-Verteilung. In der Nähe der Raumtemperatur findet ein Übergang von einer geordneten zu einer ungeordneten Phase statt. Unterhalb separiert das System in CuInSe2 und CuGaSe2. Oberhalb existiert eine gemischte Phase mit inhomogen verteilten In- und Ga-Clustern. Mit steigender Temperatur verkleinern sich die Cluster und die Homogenität nimmt zu. Bei allen Temperaturen, bis hin zur Produktionstemperatur der Solarzellen (¼ 870 K), ist In-reiches CIGS homogener als Ga-reiches CIGS. Das (Cu,In,Vac)Se-System wurde mit kanonischen und großkanonischen MC-Simulationen untersucht. Hier findet sich für das CuIn5Se8-Teilsystem ein Übergang von einer geordneten zu einer ungeordneten Phase bei T0 = 279 K. Großkanonische Simulationen mit vorgegebenen Werten für die chemischen Potentiale von Cu und In wurden verwendet, um die Konzentrations- Landschaft und damit die sich ergebenden Stöchiometrien zu bestimmen. Stabilitätsbereiche wurden für stöchiometrisches CuInSe2 und für die Defektphasen CuIn5Se8 und CuIn3Se5 bei einer Temperatur von 174 K identifiziert. Die Bereiche für die Defektphasen sind bei T = 696 K verschwunden. Die Konzentrations-Landschaft reproduziert auch die leicht Cu-armen Stöchiometrien, die bei Solarzellen mit guten Effizienzen experimentell beobachtet werden. Die Simulationsergebnisse können verwendet werden, um den industriellen CIGS-Produktionspr

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The aim of this thesis is to investigate the nature of quantum computation and the question of the quantum speed-up over classical computation by comparing two different quantum computational frameworks, the traditional quantum circuit model and the cluster-state quantum computer. After an introductory survey of the theoretical and epistemological questions concerning quantum computation, the first part of this thesis provides a presentation of cluster-state computation suitable for a philosophical audience. In spite of the computational equivalence between the two frameworks, their differences can be considered as structural. Entanglement is shown to play a fundamental role in both quantum circuits and cluster-state computers; this supports, from a new perspective, the argument that entanglement can reasonably explain the quantum speed-up over classical computation. However, quantum circuits and cluster-state computers diverge with regard to one of the explanations of quantum computation that actually accords a central role to entanglement, i.e. the Everett interpretation. It is argued that, while cluster-state quantum computation does not show an Everettian failure in accounting for the computational processes, it threatens that interpretation of being not-explanatory. This analysis presented here should be integrated in a more general work in order to include also further frameworks of quantum computation, e.g. topological quantum computation. However, what is revealed by this work is that the speed-up question does not capture all that is at stake: both quantum circuits and cluster-state computers achieve the speed-up, but the challenges that they posit go besides that specific question. Then, the existence of alternative equivalent quantum computational models suggests that the ultimate question should be moved from the speed-up to a sort of “representation theorem” for quantum computation, to be meant as the general goal of identifying the physical features underlying these alternative frameworks that allow for labelling those frameworks as “quantum computation”.

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This thesis details the development of quantum chemical methods for the accurate theoretical description of molecular systems with a complicated electronic structure. In simple cases, a single Slater determinant, in which the electrons occupy a number of energetically lowest molecular orbitals, offers a qualitatively correct model. The widely used coupled-cluster method CCSD(T) efficiently includes electron correlation effects starting from this determinant and provides reaction energies in error by only a few kJ/mol. However, the method often fails when several electronic configurations are important, as, for instance, in the course of many chemical reactions or in transition metal compounds. Internally contracted multireference coupled-cluster methods (ic-MRCC methods) cure this deficiency by using a linear combination of determinants as a reference function. Despite their theoretical elegance, the ic-MRCC equations involve thousands of terms and are therefore derived by the computer. Calculations of energy surfaces of BeH2, HF, LiF, H2O, N2 and Be3 unveil the theory's high accuracy compared to other approaches and the quality of various hierarchies of approximations. New theoretical advances include size-extensive techniques for removing linear dependencies in the ic-MRCC equations and a multireference analog of CCSD(T). Applications of the latter method to O3, Ni2O2, benzynes, C6H7NO and Cr2 underscore its potential to become a new standard method in quantum chemistry.

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In this thesis I present a new coarse-grained model suitable to investigate the phase behavior of rod-coil block copolymers on mesoscopic length scales. In this model the rods are represented by hard spherocylinders, whereas the coil block consists of interconnected beads. The interactions between the constituents are based on local densities. This facilitates an efficient Monte-Carlo sampling of the phase space. I verify the applicability of the model and the simulation approach by means of several examples. I treat pure rod systems and mixtures of rod and coil polymers. Then I append coils to the rods and investigate the role of the different model parameters. Furthermore, I compare different implementations of the model. I prove the capability of the rod-coil block copolymers in our model to exhibit typical micro-phase separated configurations as well as extraordinary phases, such as the wavy lamellar state, percolating structuresrnand clusters. Additionally, I demonstrate the metastability of the observed zigzag phase in our model. A central point of this thesis is the examination of the phase behavior of the rod-coil block copolymers in dependence of different chain lengths and interaction strengths between rods and coil. The observations of these studies are summarized in a phase diagram for rod-coil block copolymers. Furthermore, I validate a stabilization of the smectic phase with increasing coil fraction.rnIn the second part of this work I present a side project in which I derive a model permitting the simulation of tetrapods with and without grafted semiconducting block copolymers. The effect of these polymers is added in an implicit manner by effective interactions between the tetrapods. While the depletion interaction is described in an approximate manner within the Asakura-Oosawa model, the free energy penalty for the brush compression is calculated within the Alexander-de Gennes model. Recent experiments with CdSe tetrapods show that grafted tetrapods are clearly much better dispersed in the polymer matrix than bare tetrapods. My simulations confirm that bare tetrapods tend to aggregate in the matrix of excess polymers, while clustering is significantly reduced after grafting polymer chains to the tetrapods. Finally, I propose a possible extension enabling the simulation of a system with fluctuating volume and demonstrate its basic functionality. This study is originated in a cooperation with an experimental group with the goal to analyze the morphology of these systems in order to find the ideal morphology for hybrid solar cells.

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We propose an approach to optical quantum computation in which a deterministic entangling quantum gate may be performed using, on average, a few hundred coherently interacting optical elements (beam splitters, phase shifters, single photon sources, and photodetectors with feedforward). This scheme combines ideas from the optical quantum computing proposal of Knill, Laflamme, and Milburn [Nature (London) 409, 46 (2001)], and the abstract cluster-state model of quantum computation proposed by Raussendorf and Briegel [Phys. Rev. Lett. 86, 5188 (2001)].

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Normal mixture models are often used to cluster continuous data. However, conventional approaches for fitting these models will have problems in producing nonsingular estimates of the component-covariance matrices when the dimension of the observations is large relative to the number of observations. In this case, methods such as principal components analysis (PCA) and the mixture of factor analyzers model can be adopted to avoid these estimation problems. We examine these approaches applied to the Cabernet wine data set of Ashenfelter (1999), considering the clustering of both the wines and the judges, and comparing our results with another analysis. The mixture of factor analyzers model proves particularly effective in clustering the wines, accurately classifying many of the wines by location.

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This article is a short introduction to and review of the cluster-state model of quantum computation, in which coherent quantum information processing is accomplished via a sequence of single-qubit measurements applied to a fixed quantum state known as a cluster state. We also discuss a few novel properties of the model, including a proof that the cluster state cannot occur as the exact ground state of any naturally occurring physical system, and a proof that measurements on any quantum state which is linearly prepared in one dimension can be efficiently simulated on a classical computer, and thus are not candidates for use as a substrate for quantum computation.