Prediction of Queue Waiting Times for Metascheduling on Parallel Batch Systems

Prediction of queue waiting times of jobs submitted to production parallel batch systems is important to provide overall estimates to users and can also help meta-schedulers make scheduling decisions. In this work, we have developed a framework for predicting ranges of queue waiting times for jobs by employing multi-class classification of similar jobs in history. Our hierarchical prediction strategy first predicts the point wait time of a job using dynamic k-Nearest Neighbor (kNN) method. It then performs a multi-class classification using Support Vector Machines (SVMs) among all the classes of the jobs. The probabilities given by the SVM for the class predicted using k-NN and its neighboring classes are used to provide a set of ranges of predicted wait times with probabilities. We have used these predictions and probabilities in a meta-scheduling strategy that distributes jobs to different queues/sites in a multi-queue/grid environment for minimizing wait times of the jobs. Experiments with different production supercomputer job traces show that our prediction strategies can give correct predictions for about 77-87% of the jobs, and also result in about 12% improved accuracy when compared to the next best existing method. Experiments with our meta-scheduling strategy using different production and synthetic job traces for various system sizes, partitioning schemes and different workloads, show that the meta-scheduling strategy gives much improved performance when compared to existing scheduling policies by reducing the overall average queue waiting times of the jobs by about 47%.

Origin of room temperature weak-ferromagnetism in antiferromagnetic Pb(Fe2/3W1/3)O-3 ceramic

We report the origin of room temperature weak ferromagnetic behavior of polycrystalline Pb(Fe2/3W1/3)O-3 (PFW) powder. The structure and magnetic properties of the ceramic powder prepared by a Columbite method were characterized by X-ray and neutron diffraction, Mossbauer spectroscopy and magnetization measurements. Rietveld analysis of diffraction data confirm the formation of single phase PFW, without traces of any parasitic pyrochlore phase. PFW was found to crystallize in the cubic structure at room temperature. The Rietveld refinement of neutron diffraction data measured at room temperature confirmed the G-type antiferromagnetic structure of PFW in our sample. However, along with the antiferromagnetic (AFM) ordering of the Fe spins, we have observed the existence of weak ferromagnetism at room temperature through: (i) a clear opening of hysteresis (M-H) loop, (ii) bifurcation of the field cooled and zero-field cooled susceptibility; supported by Mossbauer spectroscopy results. The P-E loop measurements showed a non-linear slim hysteresis loop at room temperature due to the electronic conduction through the local inhomogeneities in the PFW crystallites and the inter-particle regions. By corroborating all the magnetic measurements, especially the spin glass nature of the sample, with the conduction behavior of the sample, we report here that the observed ferromagnetism originates at these local inhomogeneous regions in the sample, where the Fe-spins are not perfectly aligned antiferromagnetically due to the compositional disordering. (C) 2015 Elsevier Ltd and Techna Group S.r.l. All rights reserved.

Estimation of nonlinearities from pseudodynamic and dynamic responses of bridge structures using the Delay Vector Variance method

Analysis of the variability in the responses of large structural systems and quantification of their linearity or nonlinearity as a potential non-invasive means of structural system assessment from output-only condition remains a challenging problem. In this study, the Delay Vector Variance (DVV) method is used for full scale testing of both pseudo-dynamic and dynamic responses of two bridges, in order to study the degree of nonlinearity of their measured response signals. The DVV detects the presence of determinism and nonlinearity in a time series and is based upon the examination of local predictability of a signal. The pseudo-dynamic data is obtained from a concrete bridge during repair while the dynamic data is obtained from a steel railway bridge traversed by a train. We show that DVV is promising as a marker in establishing the degree to which a change in the signal nonlinearity reflects the change in the real behaviour of a structure. It is also useful in establishing the sensitivity of instruments or sensors deployed to monitor such changes. (C) 2015 Elsevier B.V. All rights reserved.

Delineation of homogeneous temperature regions: a two-stage clustering approach

Homogeneous temperature regions are necessary for use in hydrometeorological studies. The regions are often delineated by analysing statistics derived from time series of maximum, minimum or mean temperature, rather than attributes influencing temperature. This practice cannot yield meaningful regions in data-sparse areas. Further, independent validation of the delineated regions for homogeneity in temperature is not possible, as temperature records form the basis to arrive at the regions. To address these issues, a two-stage clustering approach is proposed in this study to delineate homogeneous temperature regions. First stage of the approach involves (1) determining correlation structure between observed temperature over the study area and possible predictors (large-scale atmospheric variables) influencing the temperature and (2) using the correlation structure as the basis to delineate sites in the study area into clusters. Second stage of the approach involves analysis on each of the clusters to (1) identify potential predictors (large-scale atmospheric variables) influencing temperature at sites in the cluster and (2) partition the cluster into homogeneous fuzzy temperature regions using the identified potential predictors. Application of the proposed approach to India yielded 28 homogeneous regions that were demonstrated to be effective when compared to an alternate set of 6 regions that were previously delineated over the study area. Intersite cross-correlations of monthly maximum and minimum temperatures in the existing regions were found to be weak and negative for several months, which is undesirable. This problem was not found in the case of regions delineated using the proposed approach. Utility of the proposed regions in arriving at estimates of potential evapotranspiration for ungauged locations in the study area is demonstrated.

Optimal input cross-power spectra in shake table testing of asymmetric structures

The study considers earthquake shake table testing of bending-torsion coupled structures under multi-component stationary random earthquake excitations. An experimental procedure to arrive at the optimal excitation cross-power spectral density (psd) functions which maximize/minimize the steady state variance of a chosen response variable is proposed. These optimal functions are shown to be derivable in terms of a set of system frequency response functions which could be measured experimentally without necessitating an idealized mathematical model to be postulated for the structure under study. The relationship between these optimized cross-psd functions to the most favourable/least favourable angle of incidence of seismic waves on the structure is noted. The optimal functions are also shown to be system dependent, mathematically the sharpest, and correspond to neither fully correlated motions nor independent motions. The proposed experimental procedure is demonstrated through shake table studies on two laboratory scale building frame models.

Insights into the Structural Dynamics of Nucleocytoplasmic Transport of tRNA by Exportin-t

Exportin-t (Xpot) transports mature 5'- and 3'-end processed tRNA from the nucleus to the cytoplasm by associating with a small G-protein Ran (RAs-related nuclear protein), in the nucleus. The release of tRNA in cytoplasm involves RanGTP hydrolysis. Despite the availability of crystal structures of nuclear and cytosolic forms of Xpot, the molecular details regarding the sequential events leading to tRNA release and subsequent conformational changes occurring in Xpot remain unknown. We have performed a combination of classical all-atom and accelerated molecular dynamics simulations on a set of complexes involving Xpot to study a range of features including conformational flexibility of free and cargo-bound Xpot and functionally critical contacts between Xpot and its cargo. The systems investigated include free Xpot and its different complexes, bound either to Ran (GTP/GDP) or tRNA or both. This approach provided a statistically reliable estimate of structural dynamics of Xpot after cargo release. The mechanistic basis for Xpot opening after cargo release has been explained in terms of dynamic structural hinges, about which neighboring region could be displaced to facilitate the nuclear to cytosolic state transition. Post-RanGTP hydrolysis, a cascade of events including local conformational change in RanGTP and loss of critical contacts at Xpot/tRNA interface suggest factors responsible for eventual release of tRNA. The level of flexibility in different Xpot complexes varied depending on the arrangement of individual HEAT repeats. Current study provides one of the most comprehensive and robust analysis carried out on this protein using molecular dynamics schemes.