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Visual Virology
(2012)
Effectiveness of the edge-based smoothed finite element method applied to soft biological tissues
(2012)
An increasing number of applications target their executions on specific hardware like general purpose Graphics Processing Units. Some Cloud Computing providers offer this specific hardware so that organizations can rent such resources. However, outsourcing the whole application to the Cloud causes avoidable costs if only some parts of the application benefit from the specific expensive hardware. A partial execution of applications in the Cloud is a tradeoff between costs and efficiency. This paper addresses the demand for a consistent framework that allows for a mixture of on- and off-premise calculations by migrating only specific parts to a Cloud. It uses the concept of workflows to present how individual workflow tasks can be migrated to the Cloud whereas the remaining tasks are executed on-premise.
In this article, we report on the heat-transfer resistance at interfaces as a novel, denaturation-based method to detect single-nucleotide polymorphisms in DNA. We observed that a molecular brush of double-stranded DNA grafted onto synthetic diamond surfaces does not notably affect the heat-transfer resistance at the solid-to-liquid interface. In contrast to this, molecular brushes of single-stranded DNA cause, surprisingly, a substantially higher heat-transfer resistance and behave like a thermally insulating layer. This effect can be utilized to identify ds-DNA melting temperatures via the switching from low- to high heat-transfer resistance. The melting temperatures identified with this method for different DNA duplexes (29 base pairs without and with built-in mutations) correlate nicely with data calculated by modeling. The method is fast, label-free (without the need for fluorescent or radioactive markers), allows for repetitive measurements, and can also be extended toward array formats. Reference measurements by confocal fluorescence microscopy and impedance spectroscopy confirm that the switching of heat-transfer resistance upon denaturation is indeed related to the thermal on-chip denaturation of DNA.
Many applications in computational science and engineering require the computation of eigenvalues and vectors of dense symmetric or Hermitian matrices. For example, in DFT (density functional theory) calculations on modern supercomputers 10% to 30% of the eigenvalues and eigenvectors of huge dense matrices have to be calculated. Therefore, performance and parallel scaling of the used eigensolvers is of upmost interest. In this article different routines of the linear algebra packages ScaLAPACK and Elemental for parallel solution of the symmetric eigenvalue problem are compared concerning their performance on the BlueGene/P supercomputer. Parameters for performance optimization are adjusted for the different data distribution methods used in the two libraries. It is found that for all test cases the new library Elemental which uses a two-dimensional element by element distribution of the matrices to the processors shows better performance than the old ScaLAPACK library which uses a block-cyclic distribution.