130 research outputs found

    Virtual machine scheduling in dedicated computing clusters

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    Time-critical applications process a continuous stream of input data and have to meet specific timing constraints. A common approach to ensure that such an application satisfies its constraints is over-provisioning: The application is deployed in a dedicated cluster environment with enough processing power to achieve the target performance for every specified data input rate. This approach comes with a drawback: At times of decreased data input rates, the cluster resources are not fully utilized. A typical use case is the HLT-Chain application that processes physics data at runtime of the ALICE experiment at CERN. From a perspective of cost and efficiency it is desirable to exploit temporarily unused cluster resources. Existing approaches aim for that goal by running additional applications. These approaches, however, a) lack in flexibility to dynamically grant the time-critical application the resources it needs, b) are insufficient for isolating the time-critical application from harmful side-effects introduced by additional applications or c) are not general because application-specific interfaces are used. In this thesis, a software framework is presented that allows to exploit unused resources in a dedicated cluster without harming a time-critical application. Additional applications are hosted in Virtual Machines (VMs) and unused cluster resources are allocated to these VMs at runtime. In order to avoid resource bottlenecks, the resource usage of VMs is dynamically modified according to the needs of the time-critical application. For this purpose, a number of previously not combined methods is used. On a global level, appropriate VM manipulations like hot migration, suspend/resume and start/stop are determined by an informed search heuristic and applied at runtime. Locally on cluster nodes, a feedback-controlled adaption of VM resource usage is carried out in a decentralized manner. The employment of this framework allows to increase a cluster’s usage by running additional applications, while at the same time preventing negative impact towards a time-critical application. This capability of the framework is shown for the HLT-Chain application: In an empirical evaluation the cluster CPU usage is increased from 49% to 79%, additional results are computed and no negative effect towards the HLT-Chain application are observed

    Virtual machine scheduling in dedicated computing clusters

    Get PDF
    Time-critical applications process a continuous stream of input data and have to meet specific timing constraints. A common approach to ensure that such an application satisfies its constraints is over-provisioning: The application is deployed in a dedicated cluster environment with enough processing power to achieve the target performance for every specified data input rate. This approach comes with a drawback: At times of decreased data input rates, the cluster resources are not fully utilized. A typical use case is the HLT-Chain application that processes physics data at runtime of the ALICE experiment at CERN. From a perspective of cost and efficiency it is desirable to exploit temporarily unused cluster resources. Existing approaches aim for that goal by running additional applications. These approaches, however, a) lack in flexibility to dynamically grant the time-critical application the resources it needs, b) are insufficient for isolating the time-critical application from harmful side-effects introduced by additional applications or c) are not general because application-specific interfaces are used. In this thesis, a software framework is presented that allows to exploit unused resources in a dedicated cluster without harming a time-critical application. Additional applications are hosted in Virtual Machines (VMs) and unused cluster resources are allocated to these VMs at runtime. In order to avoid resource bottlenecks, the resource usage of VMs is dynamically modified according to the needs of the time-critical application. For this purpose, a number of previously not combined methods is used. On a global level, appropriate VM manipulations like hot migration, suspend/resume and start/stop are determined by an informed search heuristic and applied at runtime. Locally on cluster nodes, a feedback-controlled adaption of VM resource usage is carried out in a decentralized manner. The employment of this framework allows to increase a cluster’s usage by running additional applications, while at the same time preventing negative impact towards a time-critical application. This capability of the framework is shown for the HLT-Chain application: In an empirical evaluation the cluster CPU usage is increased from 49% to 79%, additional results are computed and no negative effect towards the HLT-Chain application are observed

    Digenic inheritance of mutations in EPHA2 and SLC26A4 in Pendred syndrome

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    Enlarged vestibular aqueduct (EVA) is one of the most commonly identified inner ear malformations in hearing loss patients including Pendred syndrome. While biallelic mutations of the SLC26A4 gene, encoding pendrin, causes non-syndromic hearing loss with EVA or Pendred syndrome, a considerable number of patients appear to carry mono-allelic mutation. This suggests faulty pendrin regulatory machinery results in hearing loss. Here we identify EPHA2 as another causative gene of Pendred syndrome with SLC26A4. EphA2 forms a protein complex with pendrin controlling pendrin localization, which is disrupted in some pathogenic forms of pendrin. Moreover, point mutations leading to amino acid substitution in the EPHA2 gene are identified from patients bearing mono-allelic mutation of SLC26A4. Ephrin-B2 binds to EphA2 triggering internalization with pendrin inducing EphA2 autophosphorylation weakly. The identified EphA2 mutants attenuate ephrin-B2- but not ephrin-A1-induced EphA2 internalization with pendrin. Our results uncover an unexpected role of the Eph/ephrin system in epithelial function

    Smooth Muscle miRNAs Are Critical for Post-Natal Regulation of Blood Pressure and Vascular Function

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    Phenotypic modulation of smooth muscle cells (SMCs) plays a key role in vascular disease, including atherosclerosis. Several transcription factors have been suggested to regulate phenotypic modulation of SMCs but the decisive mechanisms remain unknown. Recent reports suggest that specific microRNAs (miRNAs) are involved in SMC differentiation and vascular disease but the global role of miRNAs in postnatal vascular SMC has not been elucidated. Thus, the objective of this study was to identify the role of Dicer-dependent miRNAs for blood pressure regulation and vascular SMC contractile function and differentiation in vivo. Tamoxifen-inducible and SMC specific deletion of Dicer was achieved by Cre-Lox recombination. Deletion of Dicer resulted in a global loss of miRNAs in aortic SMC. Furthermore, Dicer-deficient mice exhibited a dramatic reduction in blood pressure due to significant loss of vascular contractile function and SMC contractile differentiation as well as vascular remodeling. Several of these results are consistent with our previous observations in SM-Dicer deficient embryos. Therefore, miRNAs are essential for maintaining blood pressure and contractile function in resistance vessels. Although the phenotype of miR-143/145 deficient mice resembles the loss of Dicer, the phenotypes of SM-Dicer KO mice were far more severe suggesting that additional miRNAs are involved in maintaining postnatal SMC differentiation

    Long-range angular correlations on the near and away side in p–Pb collisions at

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    Azimuthal anisotropy of charged jet production in root s(NN)=2.76 TeV Pb-Pb collisions

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    We present measurements of the azimuthal dependence of charged jet production in central and semi-central root s(NN) = 2.76 TeV Pb-Pb collisions with respect to the second harmonic event plane, quantified as nu(ch)(2) (jet). Jet finding is performed employing the anti-k(T) algorithm with a resolution parameter R = 0.2 using charged tracks from the ALICE tracking system. The contribution of the azimuthal anisotropy of the underlying event is taken into account event-by-event. The remaining (statistical) region-to-region fluctuations are removed on an ensemble basis by unfolding the jet spectra for different event plane orientations independently. Significant non-zero nu(ch)(2) (jet) is observed in semi-central collisions (30-50% centrality) for 20 <p(T)(ch) (jet) <90 GeV/c. The azimuthal dependence of the charged jet production is similar to the dependence observed for jets comprising both charged and neutral fragments, and compatible with measurements of the nu(2) of single charged particles at high p(T). Good agreement between the data and predictions from JEWEL, an event generator simulating parton shower evolution in the presence of a dense QCD medium, is found in semi-central collisions. (C) 2015 CERN for the benefit of the ALICE Collaboration. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).Peer reviewe

    Forward-central two-particle correlations in p-Pb collisions at root s(NN)=5.02 TeV

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    Two-particle angular correlations between trigger particles in the forward pseudorapidity range (2.5 2GeV/c. (C) 2015 CERN for the benefit of the ALICE Collaboration. Published by Elsevier B. V.Peer reviewe

    Event-shape engineering for inclusive spectra and elliptic flow in Pb-Pb collisions at root(NN)-N-S=2.76 TeV

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    Pseudorapidity and transverse-momentum distributions of charged particles in proton-proton collisions at root s=13 TeV

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    The pseudorapidity (eta) and transverse-momentum (p(T)) distributions of charged particles produced in proton-proton collisions are measured at the centre-of-mass energy root s = 13 TeV. The pseudorapidity distribution in vertical bar eta vertical bar <1.8 is reported for inelastic events and for events with at least one charged particle in vertical bar eta vertical bar <1. The pseudorapidity density of charged particles produced in the pseudorapidity region vertical bar eta vertical bar <0.5 is 5.31 +/- 0.18 and 6.46 +/- 0.19 for the two event classes, respectively. The transverse-momentum distribution of charged particles is measured in the range 0.15 <p(T) <20 GeV/c and vertical bar eta vertical bar <0.8 for events with at least one charged particle in vertical bar eta vertical bar <1. The evolution of the transverse momentum spectra of charged particles is also investigated as a function of event multiplicity. The results are compared with calculations from PYTHIA and EPOS Monte Carlo generators. (C) 2015 CERN for the benefit of the ALICE Collaboration. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).Peer reviewe

    Elliptic flow of muons from heavy-flavour hadron decays at forward rapidity in Pb-Pb collisions at root s(NN)=2.76TeV

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    The elliptic flow, v(2), of muons from heavy-flavour hadron decays at forward rapidity (2.5 <y <4) is measured in Pb-Pb collisions at root s(NN)= 2.76TeVwith the ALICE detector at the LHC. The scalar product, two- and four-particle Q cumulants and Lee-Yang zeros methods are used. The dependence of the v(2) of muons from heavy-flavour hadron decays on the collision centrality, in the range 0-40%, and on transverse momentum, p(T), is studied in the interval 3 <p(T)<10 GeV/c. A positive v(2) is observed with the scalar product and two-particle Q cumulants in semi-central collisions (10-20% and 20-40% centrality classes) for the p(T) interval from 3 to about 5GeV/c with a significance larger than 3 sigma, based on the combination of statistical and systematic uncertainties. The v(2) magnitude tends to decrease towards more central collisions and with increasing pT. It becomes compatible with zero in the interval 6 <p(T)<10 GeV/c. The results are compared to models describing the interaction of heavy quarks and open heavy-flavour hadrons with the high-density medium formed in high-energy heavy-ion collisions. (C) 2015 CERN for the benefit of the ALICE Collaboration. Published by Elsevier B.V.Peer reviewe
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