189,671 research outputs found
Predicting glaucomatous visual field deterioration through short multivariate time series modelling
In bio-medical domains there are many
applications involving the modelling of
multivariate time series (MTS) data. One area
that has been largely overlooked so far is the
particular type of time series where the data set
consists of a large number of variables but with
a small number of observations. In this paper we
describe the development of a novel computational
method based on genetic algorithms that bypasses
the size restrictions of traditional statistical
MTS methods, makes no distribution assumptions,
and also locates the order and associated
parameters as a whole step. We apply this method to the prediction and modelling of glaucomatous
visual field deterioration
Inner product computation for sparse iterative solvers on\ud distributed supercomputer
Recent years have witnessed that iterative Krylov methods without re-designing are not suitable for distribute supercomputers because of intensive global communications. It is well accepted that re-engineering Krylov methods for prescribed computer architecture is necessary and important to achieve higher performance and scalability. The paper focuses on simple and practical ways to re-organize Krylov methods and improve their performance for current heterogeneous distributed supercomputers. In construct with most of current software development of Krylov methods which usually focuses on efficient matrix vector multiplications, the paper focuses on the way to compute inner products on supercomputers and explains why inner product computation on current heterogeneous distributed supercomputers is crucial for scalable Krylov methods. Communication complexity analysis shows that how the inner product computation can be the bottleneck of performance of (inner) product-type iterative solvers on distributed supercomputers due to global communications. Principles of reducing such global communications are discussed. The importance of minimizing communications is demonstrated by experiments using up to 900 processors. The experiments were carried on a Dawning 5000A, one of the fastest and earliest heterogeneous supercomputers in the world. Both the analysis and experiments indicates that inner product computation is very likely to be the most challenging kernel for inner product-based iterative solvers to achieve exascale
Minimizing synchronizations in sparse iterative solvers for distributed supercomputers
Eliminating synchronizations is one of the important techniques related to minimizing communications for modern high performance computing. This paper discusses principles of reducing communications due to global synchronizations in sparse iterative solvers on distributed supercomputers. We demonstrates how to minimizing global synchronizations by rescheduling a typical Krylov subspace method. The benefit of minimizing synchronizations is shown in theoretical analysis and is verified by numerical experiments using up to 900 processors. The experiments also show the communication complexity for some structured sparse matrix vector multiplications and global communications in the underlying supercomputers are in the order P1/2.5 and P4/5 respectively, where P is the number of processors and the experiments were carried on a Dawning 5000A
Disorder effects on the spin-Hall current in a diffusive Rashba two-dimensional heavy-hole system
We investigate the spin-Hall effect in a two-dimensional heavy-hole system
with Rashba spin-orbit coupling using a nonequilibrium Green's function
approach. Both the short- and long-range disorder scatterings are considered in
the self-consistent Born approximation. We find that, in the case of long-range
collisions, the disorder-mediated process leads to an enhancement of the
spin-Hall current at high heavy-hole density, whereas for short-range
scatterings it gives a vanishing contribution. This result suggests that the
recently observed spin-Hall effect in experiment is a result of the sum of the
intrinsic and disorder-mediated contributions. We have also calculated the
temperature dependence of spin-Hall conductivity, which reveals a decrease with
increasing the temperature.Comment: 5 pages, 2 figures, Typos in the values of hole density correcte
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Variable grouping in multivariate time series via correlation
The decomposition of high-dimensional multivariate time series (MTS) into a number of low-dimensional MTS is a useful but challenging task because the number of possible dependencies between variables is likely to be huge. This paper is about a systematic study of the “variable groupings” problem in MTS. In particular, we investigate different methods of utilizing the information regarding correlations among MTS variables. This type of method does not appear to have been studied before. In all, 15 methods are suggested and applied to six datasets where there are identifiable mixed groupings of MTS variables. This paper describes the general methodology, reports extensive experimental results, and concludes with useful insights on the strength and weakness of this type of grouping metho
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