806 resultados para structured parallel computations


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In this paper we present an algorithm for the numerical simulation of the cavitation in the hydrodynamic lubrication of journal bearings. Despite the fact that this physical process is usually modelled as a free boundary problem, we adopted the equivalent variational inequality formulation. We propose a two-level iterative algorithm, where the outer iteration is associated to the penalty method, used to transform the variational inequality into a variational equation, and the inner iteration is associated to the conjugate gradient method, used to solve the linear system generated by applying the finite element method to the variational equation. This inner part was implemented using the element by element strategy, which is easily parallelized. We analyse the behavior of two physical parameters and discuss some numerical results. Also, we analyse some results related to the performance of a parallel implementation of the algorithm.

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The results of a numerical study of premixed Hydrogen-air flows ignition by an oblique shock wave (OSW) stabilized by a wedge are presented, in situations when initial and boundary conditions are such that transition between the initial OSW and an oblique detonation wave (ODW) is observed. More precisely, the objectives of the paper are: (i) to identify the different possible structures of the transition region that exist between the initial OSW and the resulting ODW and (ii) to evidence the effect on the ODW of an abrupt decrease of the wedge angle in such a way that the final part of the wedge surface becomes parallel to the initial flow. For such a geometrical configuration and for the initial and boundary conditions considered, the overdriven detonation supported by the initial wedge angle is found to relax towards a Chapman-Jouguet detonation in the region where the wedge surface is parallel to the initial flow. Computations are performed using an adaptive, unstructured grid, finite volume computer code previously developed for the sake of the computations of high speed, compressible flows of reactive gas mixtures. Physico-chemical properties are functions of the local mixture composition, temperature and pressure, and they are computed using the CHEMKIN-II subroutines.

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In this paper we present a study of feasibility by using Cassino Parallel Manipulator (CaPaMan) as an earthquake simulator. We propose a suitable formulation to simulate the frequency, amplitude and acceleration magnitude of seismic motion by means of the movable platform motion by giving a suitable input motion. In this paper we have reported numerical simulations that simulate the three principal earthquake types for a seismic motion: one at the epicenter (having a vertical motion), another far from the epicenter (with the motion on a horizontal plane), and a combined general motion (with a vertical and horizontal motion).

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The pumping processes requiring wide range of flow are often equipped with parallelconnected centrifugal pumps. In parallel pumping systems, the use of variable speed control allows that the required output for the process can be delivered with a varying number of operated pump units and selected rotational speed references. However, the optimization of the parallel-connected rotational speed controlled pump units often requires adaptive modelling of both parallel pump characteristics and the surrounding system in varying operation conditions. The available information required for the system modelling in typical parallel pumping applications such as waste water treatment and various cooling and water delivery pumping tasks can be limited, and the lack of real-time operation point monitoring often sets limits for accurate energy efficiency optimization. Hence, alternatives for easily implementable control strategies which can be adopted with minimum system data are necessary. This doctoral thesis concentrates on the methods that allow the energy efficient use of variable speed controlled parallel pumps in system scenarios in which the parallel pump units consist of a centrifugal pump, an electric motor, and a frequency converter. Firstly, the suitable operation conditions for variable speed controlled parallel pumps are studied. Secondly, methods for determining the output of each parallel pump unit using characteristic curve-based operation point estimation with frequency converter are discussed. Thirdly, the implementation of the control strategy based on real-time pump operation point estimation and sub-optimization of each parallel pump unit is studied. The findings of the thesis support the idea that the energy efficiency of the pumping can be increased without the installation of new, more efficient components in the systems by simply adopting suitable control strategies. An easily implementable and adaptive control strategy for variable speed controlled parallel pumping systems can be created by utilizing the pump operation point estimation available in modern frequency converters. Hence, additional real-time flow metering, start-up measurements, and detailed system model are unnecessary, and the pumping task can be fulfilled by determining a speed reference for each parallel-pump unit which suggests the energy efficient operation of the pumping system.

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In this work, superconducting YBa2 Cu3O6+x (YBCO) thin films have been studied with the experimental focus on the anisotropy of BaZrO3 (BZO) doped YBCOthin films and the theoretical focus on modelling flux pinning by numerically solving Ginzburg- Landau equations. Also, the structural properties of undoped YBCO thin films grown on NdGaO3 (NGO) and MgO substrates were investigated. The thin film samples were made by pulsed laser ablation on single crystal substrates. The structural properties of the thin films were characterized by X-ray diffraction and atomic force microscope measurements. The superconducting properties were investigated with a magnetometer and also with transport measurements in pulsed magnetic field up to 30 T. Flux pinning was modelled by restricting the value of the order parameter inside the columnar pinning sites and then solving the Ginzburg-Landau equations numerically with the restrictions in place. The computations were done with a parallel code on a supercomputer. The YBCO thin films were seen to develop microcracks when grown on NGO or MgO substrates. The microcrack formation was connected to the structure of the YBCO thin films in both cases. Additionally, the microcracks can be avoided by careful optimization of the deposition parameters and the film thickness. The BZO doping of the YBCO thin films was seen to decrease the effective electron mass anisotropy, which was seen by fitting the Blatter scaling to the angle dependence of the upper critical field. The Ginzburg-Landau simulations were able to reproduce the measured magnetic field dependence of the critical current density for BZO doped and undoped YBCO. The simulations showed that in addition to the large density also the large size of the BZO nanorods is a key factor behind the change in the power law behaviour between BZO doped and undoped YBCO. Additionally, the Ginzburg-Landau equations were solved for type I thin films where giant vortices were seen to appear depending on the film thickness. The simulations predicted that singly quantized vortices are stable in type I films up to quite large thicknesses and that the size of the vortices increases with decreasing film thickness, in a way that is similar to the behaviour of the interaction length of Pearl vortices.

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Vaikka liiketoimintatiedon hallintaa sekä johdon päätöksentekoa on tutkittu laajasti, näiden kahden käsitteen yhteisvaikutuksesta on olemassa hyvin rajallinen määrä tutkimustietoa. Tulevaisuudessa aiheen tärkeys korostuu, sillä olemassa olevan datan määrä kasvaa jatkuvasti. Yritykset tarvitsevat jatkossa yhä enemmän kyvykkyyksiä sekä resursseja, jotta sekä strukturoitua että strukturoimatonta tietoa voidaan hyödyntää lähteestä riippumatta. Nykyiset Business Intelligence -ratkaisut mahdollistavat tehokkaan liiketoimintatiedon hallinnan osana johdon päätöksentekoa. Aiemman kirjallisuuden pohjalta, tutkimuksen empiirinen osuus tunnistaa liiketoimintatiedon hyödyntämiseen liittyviä tekijöitä, jotka joko tukevat tai rajoittavat johdon päätöksentekoprosessia. Tutkimuksen teoreettinen osuus johdattaa lukijan tutkimusaiheeseen kirjallisuuskatsauksen avulla. Keskeisimmät tutkimukseen liittyvät käsitteet, kuten Business Intelligence ja johdon päätöksenteko, esitetään relevantin kirjallisuuden avulla – tämän lisäksi myös dataan liittyvät käsitteet analysoidaan tarkasti. Tutkimuksen empiirinen osuus rakentuu tutkimusteorian pohjalta. Tutkimuksen empiirisessä osuudessa paneudutaan tutkimusteemoihin käytännön esimerkein: kolmen tapaustutkimuksen avulla tutkitaan sekä kuvataan toisistaan irrallisia tapauksia. Jokainen tapaus kuvataan sekä analysoidaan teoriaan perustuvien väitteiden avulla – nämä väitteet ovat perusedellytyksiä menestyksekkäälle liiketoimintatiedon hyödyntämiseen perustuvalle päätöksenteolle. Tapaustutkimusten avulla alkuperäistä tutkimusongelmaa voidaan analysoida tarkasti huomioiden jo olemassa oleva tutkimustieto. Analyysin tulosten avulla myös yksittäisiä rajoitteita sekä mahdollistavia tekijöitä voidaan analysoida. Tulokset osoittavat, että rajoitteilla on vahvasti negatiivinen vaikutus päätöksentekoprosessin onnistumiseen. Toisaalta yritysjohto on tietoinen liiketoimintatiedon hallintaan liittyvistä positiivisista seurauksista, vaikka kaikkia mahdollisuuksia ei olisikaan hyödynnetty. Tutkimuksen merkittävin tulos esittelee viitekehyksen, jonka puitteissa johdon päätöksentekoprosesseja voidaan arvioida sekä analysoida. Despite the fact that the literature on Business Intelligence and managerial decision-making is extensive, relatively little effort has been made to research the relationship between them. This particular field of study has become important since the amount of data in the world is growing every second. Companies require capabilities and resources in order to utilize structured data and unstructured data from internal and external data sources. However, the present Business Intelligence technologies enable managers to utilize data effectively in decision-making. Based on the prior literature, the empirical part of the thesis identifies the enablers and constraints in computer-aided managerial decision-making process. In this thesis, the theoretical part provides a preliminary understanding about the research area through a literature review. The key concepts such as Business Intelligence and managerial decision-making are explored by reviewing the relevant literature. Additionally, different data sources as well as data forms are analyzed in further detail. All key concepts are taken into account when the empirical part is carried out. The empirical part obtains an understanding of the real world situation when it comes to the themes that were covered in the theoretical part. Three selected case companies are analyzed through those statements, which are considered as critical prerequisites for successful computer-aided managerial decision-making. The case study analysis, which is a part of the empirical part, enables the researcher to examine the relationship between Business Intelligence and managerial decision-making. Based on the findings of the case study analysis, the researcher identifies the enablers and constraints through the case study interviews. The findings indicate that the constraints have a highly negative influence on the decision-making process. In addition, the managers are aware of the positive implications that Business Intelligence has for decision-making, but all possibilities are not yet utilized. As a main result of this study, a data-driven framework for managerial decision-making is introduced. This framework can be used when the managerial decision-making processes are evaluated and analyzed.

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Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

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Parallel-connected photovoltaic inverters are required in large solar plants where it is not economically or technically reasonable to use a single inverter. Currently, parallel inverters require individual isolating transformers to cut the path for the circulating current. In this doctoral dissertation, the problem is approached by attempting to minimize the generated circulating current. The circulating current is a function of the generated common-mode voltages of the parallel inverters and can be minimized by synchronizing the inverters. The synchronization has previously been achieved by a communication link. However, in photovoltaic systems the inverters may be located far apart from each other. Thus, a control free of communication is desired. It is shown in this doctoral dissertation that the circulating current can also be obtained by a common-mode voltage measurement. A control method based on a short-time switching frequency transition is developed and tested with an actual photovoltaic environment of two parallel inverters connected to two 5 kW solar arrays. Controls based on the measurement of the circulating current and the common-mode voltage are generated and tested. A communication-free method of controlling the circulating current between parallelconnected inverters is developed and verified.

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The dissertation proposes two control strategies, which include the trajectory planning and vibration suppression, for a kinematic redundant serial-parallel robot machine, with the aim of attaining the satisfactory machining performance. For a given prescribed trajectory of the robot's end-effector in the Cartesian space, a set of trajectories in the robot's joint space are generated based on the best stiffness performance of the robot along the prescribed trajectory. To construct the required system-wide analytical stiffness model for the serial-parallel robot machine, a variant of the virtual joint method (VJM) is proposed in the dissertation. The modified method is an evolution of Gosselin's lumped model that can account for the deformations of a flexible link in more directions. The effectiveness of this VJM variant is validated by comparing the computed stiffness results of a flexible link with the those of a matrix structural analysis (MSA) method. The comparison shows that the numerical results from both methods on an individual flexible beam are almost identical, which, in some sense, provides mutual validation. The most prominent advantage of the presented VJM variant compared with the MSA method is that it can be applied in a flexible structure system with complicated kinematics formed in terms of flexible serial links and joints. Moreover, by combining the VJM variant and the virtual work principle, a systemwide analytical stiffness model can be easily obtained for mechanisms with both serial kinematics and parallel kinematics. In the dissertation, a system-wide stiffness model of a kinematic redundant serial-parallel robot machine is constructed based on integration of the VJM variant and the virtual work principle. Numerical results of its stiffness performance are reported. For a kinematic redundant robot, to generate a set of feasible joints' trajectories for a prescribed trajectory of its end-effector, its system-wide stiffness performance is taken as the constraint in the joints trajectory planning in the dissertation. For a prescribed location of the end-effector, the robot permits an infinite number of inverse solutions, which consequently yields infinite kinds of stiffness performance. Therefore, a differential evolution (DE) algorithm in which the positions of redundant joints in the kinematics are taken as input variables was employed to search for the best stiffness performance of the robot. Numerical results of the generated joint trajectories are given for a kinematic redundant serial-parallel robot machine, IWR (Intersector Welding/Cutting Robot), when a particular trajectory of its end-effector has been prescribed. The numerical results show that the joint trajectories generated based on the stiffness optimization are feasible for realization in the control system since they are acceptably smooth. The results imply that the stiffness performance of the robot machine deviates smoothly with respect to the kinematic configuration in the adjacent domain of its best stiffness performance. To suppress the vibration of the robot machine due to varying cutting force during the machining process, this dissertation proposed a feedforward control strategy, which is constructed based on the derived inverse dynamics model of target system. The effectiveness of applying such a feedforward control in the vibration suppression has been validated in a parallel manipulator in the software environment. The experimental study of such a feedforward control has also been included in the dissertation. The difficulties of modelling the actual system due to the unknown components in its dynamics is noticed. As a solution, a back propagation (BP) neural network is proposed for identification of the unknown components of the dynamics model of the target system. To train such a BP neural network, a modified Levenberg-Marquardt algorithm that can utilize an experimental input-output data set of the entire dynamic system is introduced in the dissertation. Validation of the BP neural network and the modified Levenberg- Marquardt algorithm is done, respectively, by a sinusoidal output approximation, a second order system parameters estimation, and a friction model estimation of a parallel manipulator, which represent three different application aspects of this method.

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We have developed a software called pp-Blast that uses the publicly available Blast package and PVM (parallel virtual machine) to partition a multi-sequence query across a set of nodes with replicated or shared databases. Benchmark tests show that pp-Blast running in a cluster of 14 PCs outperformed conventional Blast running in large servers. In addition, using pp-Blast and the cluster we were able to map all human cDNAs onto the draft of the human genome in less than 6 days. We propose here that the cost/benefit ratio of pp-Blast makes it appropriate for large-scale sequence analysis. The source code and configuration files for pp-Blast are available at http://www.ludwig.org.br/biocomp/tools/pp-blast.

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This thesis presents a novel design paradigm, called Virtual Runtime Application Partitions (VRAP), to judiciously utilize the on-chip resources. As the dark silicon era approaches, where the power considerations will allow only a fraction chip to be powered on, judicious resource management will become a key consideration in future designs. Most of the works on resource management treat only the physical components (i.e. computation, communication, and memory blocks) as resources and manipulate the component to application mapping to optimize various parameters (e.g. energy efficiency). To further enhance the optimization potential, in addition to the physical resources we propose to manipulate abstract resources (i.e. voltage/frequency operating point, the fault-tolerance strength, the degree of parallelism, and the configuration architecture). The proposed framework (i.e. VRAP) encapsulates methods, algorithms, and hardware blocks to provide each application with the abstract resources tailored to its needs. To test the efficacy of this concept, we have developed three distinct self adaptive environments: (i) Private Operating Environment (POE), (ii) Private Reliability Environment (PRE), and (iii) Private Configuration Environment (PCE) that collectively ensure that each application meets its deadlines using minimal platform resources. In this work several novel architectural enhancements, algorithms and policies are presented to realize the virtual runtime application partitions efficiently. Considering the future design trends, we have chosen Coarse Grained Reconfigurable Architectures (CGRAs) and Network on Chips (NoCs) to test the feasibility of our approach. Specifically, we have chosen Dynamically Reconfigurable Resource Array (DRRA) and McNoC as the representative CGRA and NoC platforms. The proposed techniques are compared and evaluated using a variety of quantitative experiments. Synthesis and simulation results demonstrate VRAP significantly enhances the energy and power efficiency compared to state of the art.

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Myocardial ischemia, as well as the induction agents used in anesthesia, may cause corrected QT interval (QTc) prolongation. The objective of this randomized, double-blind trial was to determine the effects of high- vs conventional-dose bolus rocuronium on QTc duration and the incidence of dysrhythmias following anesthesia induction and intubation. Fifty patients about to undergo coronary artery surgery were randomly allocated to receive conventional-dose (0.6 mg/kg, group C, n=25) or high-dose (1.2 mg/kg, group H, n=25) rocuronium after induction with etomidate and fentanyl. QTc, heart rate, and mean arterial pressure were recorded before induction (T0), after induction (T1), after rocuronium (just before laryngoscopy; T2), 2 min after intubation (T3), and 5 min after intubation (T4). The occurrence of dysrhythmias was recorded. In both groups, QTc was significantly longer at T3 than at baseline [475 vs 429 ms in group C (P=0.001), and 459 vs 434 ms in group H (P=0.005)]. The incidence of dysrhythmias in group C (28%) and in group H (24%) was similar. The QTc after high-dose rocuronium was not significantly longer than after conventional-dose rocuronium in patients about to undergo coronary artery surgery who were induced with etomidate and fentanyl. In both groups, compared with baseline, QTc was most prolonged at 2 min after intubation, suggesting that QTc prolongation may be due to the nociceptive stimulus of intubation.

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Neoadjuvant chemotherapy has practical and theoretical advantages over adjuvant chemotherapy strategy in breast cancer (BC) management. Moreover, metronomic delivery has a more favorable toxicity profile. The present study examined the feasibility of neoadjuvant metronomic chemotherapy in two cohorts [HER2+ (TraQme) and HER2− (TAME)] of locally advanced BC. Twenty patients were prospectively enrolled (TraQme, n=9; TAME, n=11). Both cohorts received weekly paclitaxel at 100 mg/m2 during 8 weeks followed by weekly doxorubicin at 24 mg/m2 for 9 weeks in combination with oral cyclophosphamide at 100 mg/day (fixed dose). The HER2+ cohort received weekly trastuzumab. The study was interrupted because of safety issues. Thirty-six percent of patients in the TAME cohort and all patients from the TraQme cohort had stage III BC. Of note, 33% from the TraQme cohort and 66% from the TAME cohort displayed hormone receptor positivity in tumor tissue. The pathological complete response rates were 55% and 18% among patients enrolled in the TraQme and TAME cohorts, respectively. Patients in the TraQme cohort had more advanced BC stages at diagnosis, higher-grade pathological classification, and more tumors lacking hormone receptor expression, compared to the TAME cohort. The toxicity profile was also different. Two patients in the TraQme cohort developed pneumonitis, and in the TAME cohort we observed more hematological toxicity and hand-foot syndrome. The neoadjuvant metronomic chemotherapy regimen evaluated in this trial was highly effective in achieving a tumor response, especially in the HER2+ cohort. Pneumonitis was a serious, unexpected adverse event observed in this group. Further larger and randomized trials are warranted to evaluate the association between metronomic chemotherapy and trastuzumab treatment.

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The whole research of the current Master Thesis project is related to Big Data transfer over Parallel Data Link and my main objective is to assist the Saint-Petersburg National Research University ITMO research team to accomplish this project and apply Green IT methods for the data transfer system. The goal of the team is to transfer Big Data by using parallel data links with SDN Openflow approach. My task as a team member was to compare existing data transfer applications in case to verify which results the highest data transfer speed in which occasions and explain the reasons. In the context of this thesis work a comparison between 5 different utilities was done, which including Fast Data Transfer (FDT), BBCP, BBFTP, GridFTP, and FTS3. A number of scripts where developed which consist of creating random binary data to be incompressible to have fair comparison between utilities, execute the Utilities with specified parameters, create log files, results, system parameters, and plot graphs to compare the results. Transferring such an enormous variety of data can take a long time, and hence, the necessity appears to reduce the energy consumption to make them greener. In the context of Green IT approach, our team used Cloud Computing infrastructure called OpenStack. It’s more efficient to allocated specific amount of hardware resources to test different scenarios rather than using the whole resources from our testbed. Testing our implementation with OpenStack infrastructure results that the virtual channel does not consist of any traffic and we can achieve the highest possible throughput. After receiving the final results we are in place to identify which utilities produce faster data transfer in different scenarios with specific TCP parameters and we can use them in real network data links.