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An efficient geosciences workflow on multi-core processors and GPUs:a case study for aerosol optical depth retrieval from MODIS satellite data

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International Journal of Digital Earth 2016年第8期9卷 748-765页

作者： Jia Liu Dustin Feld Yong Xue Jochen Garcke Thomas Soddemann Peiyuan Pan Key Laboratory of Digital Earth Science Institute of Remote Sensing and Digital EarthChinese Academy of SciencesBeijingChina Faculty of Life Sciences and Computing London Metropolitan UniversityLondonUK Fraunhofer Institute for Algorithms and Scientific Computing SCAI Sankt AugustinGermany Institute for Numerical Simulation University of BonnBonnGermany University of Chinese Academy of Sciences BeijingChina Department of Computer Science University of CologneCologneGermany

Quantitative remote sensing retrieval algorithms help understanding the dynamic aspects of Digital ***,the Big Data and complex models in Digital Earth pose grand challenges for computation *** this article,taking the aerosol optical depth(AOD)retrieval as a study case,we exploit parallel computing methods for high efficient geophysical parameter *** present an efficient geocomputation workflow for the AOD calculation from the Moderate Resolution Imaging Spectroradiometer(MODIS)satellite *** to their individual potential for parallelization,several procedures were adapted and implemented for a successful parallel execution on multicore processors and Graphics Processing Units(GPUs).The benchmarks in this paper validate the high parallel performance of the retrieval workflow with speedups of up to 5.x on a multi-core processor with 8 threads and 43.x on a *** specifically address the time-consuming model retrieval part,hybrid parallel patterns which combine the multicore processor’s and the GPU’s compute power were implemented with static and dynamic workload distributions and evaluated on two systems with different CPU–GPU *** is shown that only the dynamic hybrid implementation leads to a greatly enhanced overall exploitation of the heterogeneous hardware environment in varying circumstances.

关键词： Digital earth highperformance computing GPU multi-core hybrid parallel pattern aerosol optical depth retrieval workflow

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Improving profile-profile alignments via log average scoring 1

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1st International Workshop on algorithms in Bioinformatics, WABI 2001

作者： Von Öhsen, Niklas Zimmer, Ralf SCAI-Institute for Algorithms and Scientific Computing GMD-German National Research Center for Information Technology Schloss Birlinghoven Sankt Augustin53754 Germany

ISBN: (数字)9783540446965

ISBN: (纸本)3540425160

Alignments of frequency profiles against frequency profiles have a wide scope of applications in currently used bioinformatic analysis tools ranging from multiple alignment methods based on the progressive alignment approach to detecting of structural similarities based on remote sequence homology. We present the new log average scoring approach to calculating the score to be used with alignment algorithms like dynamic programming and show that it significantly outperforms the commonly used average scoring and dot product approach on a fold recognition benchmark. The score is also applicable to the problem of aligning two multiple alignments since every multiple alignment induces a frequency profile. © Springer-Verlag Berlin Heidelberg 2001.

关键词： Dynamic programming

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Adaptive parallel multigrid in computational fluid dynamics

Adaptive parallel multigrid in computational fluid dynamics

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Proceedings of the International Conference and Exhibition on High-Performance computing and Networking

作者： Wu, J. Institute for Algorithms and Scientific Computing (SCAI) GMD-German National Research Center for Information Technology SchloßBirlinghoven Sankt Augustin 53754 Germany

ISBN: (纸本)9783540611424

In this paper the numerical and parallel efficiency of the adaptive parallel strategy employed in a multigrid-solver package LiSS, developed in GMD-scai, are discussed. Two main aspects in these issues are adaptive criterion and data-redistribution concept for load balancing. The adaptive criterion is based on the finite-element-residuals of governing equations. It can find refinement regions automatically, e.g. near shocks and geometric singularities. For parallelization new data in the adaptive phase can be re-distributed by sub-dividing and remapping the sub-blocks onto exisiting processors to obtain approximate load balancing. The 2D exmaples of Euler equations and incompressible Navier- Stokes equations in this paper show obviously high numerical and parallel efficiency of LiSS. © Springer-Verlag Berlin Heidelberg 1996.

关键词： Navier Stokes equations

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Cell-centred multigrid revisited

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computing and Visualization in Science 2004年第3期7卷 129-140页

作者： Marcus Mohr Roman Wienands Friedrich-Alexander-University of Erlangen-Nuremberg Erlangen Germany Fraunhofer Institute for Algorithms and Scientific Computing (SCAI) Sankt Augustin Germany

In this paper we treat the cell-centred multigrid approach, which distinguishes itself from the classical vertex-centred multigrid by a non-nested hierarchy of grid nodes and the use of constant, problem-independent transfer operators even in complicated situations. We demonstrate, that the tool of Local Fourier Analysis can also be profitably applied in this setting. We consider in detail the standard transfer operators from literature and their respective polynomial and Fourier orders, paying special attention to the combination of piecewise constant interpolation and its adjoint. Furthermore, we give several numerical examples for model problems and an application from biomedical engineering.

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Optimization of retrieval algorithms on large scale knowledge graphs

arXiv

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arXiv 2020年

作者： Dörpinghaus, Jens Stefan, Andreas Fraunhofer Institute for Algorithms and Scientific Computing SCAI Schloss Birlinghoven Sankt Augustin Germany

Knowledge graphs have been shown to play an important role in recent knowledge mining and discovery, for example in the field of life sciences or bioinformatics. Although a lot of research has been done on the field of query optimization, query transformation and of course in storing and retrieving large scale knowledge graphs the field of algorithmic optimization is still a major challenge and a vital factor in using graph databases. Few researchers have addressed the problem of optimizing algorithms on large scale labeled property graphs. Here, we present two optimization approaches and compare them with a naive approach of directly querying the graph database. The aim of our work is to determine limiting factors of graph databases like Neo4j and we describe a novel solution to tackle these challenges. For this, we suggest a classification schema to differ between the complexity of a problem on a graph database. We evaluate our optimization approaches on a test system containing a knowledge graph derived biomedical publication data enriched with text mining data. This dense graph has more than 71M nodes and 850M relationships. The results are very encouraging and – depending on the problem – we were able to show a speedup of a factor between 44 and 3839. Copyright © 2020, The Authors. All rights reserved.

关键词： Knowledge graph

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Towards context in large scale biomedical knowledge graphs

arXiv

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arXiv 2020年

作者： Dörpinghaus, Jens Stefan, Andreas Schultz, Bruce Jacobs, Marc Fraunhofer Institute for Algorithms and Scientific Computing SCAI Schloss Birlinghoven Sankt Augustin Germany

Contextual information is widely considered for NLP and knowledge discovery in life sciences since it highly influences the exact meaning of natural language. The scientific challenge is not only to extract such context data, but also to store this data for further query and discovery approaches. Here, we propose a multiple step knowledge graph approach using labeled property graphs based on polyglot persistence systems to utilize context data for context mining, graph queries, knowledge discovery and extraction. We introduce the graph-theoretic foundation for a general context concept within semantic networks and show a proof-of-concept based on biomedical literature and text mining. Our test system contains a knowledge graph derived from the entirety of PubMed and scaiView data and is enriched with text mining data and domain specific language data using BEL. Here, context is a more general concept than annotations. This dense graph has more than 71M nodes and 850M relationships. We discuss the impact of this novel approach with 27 real world use cases represented by graph queries. Copyright © 2020, The Authors. All rights reserved.

关键词： Data mining

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Information extraction technologies for the life science industry

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Drug Discovery Today: Technologies 2005年第3期2卷 217-224页

作者： Fluck, Juliane Zimmermann, Marc Kurapkat, Günther Hofmann, Martin Fraunhofer-Institute for Algorithms and Scientific Computing 53754 Sankt Augustin Germany TEMIS Deutschland GmbH 69115 Heidelberg Kurfürstenanlage 3 Germany

Access to relevant information and knowledge is essential for all steps of the drug discovery process. However, keeping track of relevant information in publications and patents becomes a real challenge for scientists and managers in industrial research. Computer-aided information extraction (IE) systems have been developed to support the work of scientists by extracting relevant information from scientific publications and presenting it in an aggregated, condensed form. In this review, we will give an overview on current information extraction strategies in the life sciences with a special focus on biological entity recognition and more recent developments towards the identification and extraction of chemical compound names and structures. © 2005 Elsevier Ltd. All rights reserved.

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Parameter Identification in Cyclic Voltammetry of Alkaline Methanol Oxidation 8

Parameter Identification in Cyclic Voltammetry of Alkaline M...

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8th International Conference on Simulation and Modeling Methodologies, Technologies and Applications, SIMULTECH 2018

作者： Clees, Tanja Nikitin, Igor Nikitina, Lialia Pott, Sabine Krewer, Ulrike Haisch, Theresa Fraunhofer Institute for Algorithms and Scientific Computing Sankt Augustin Germany Institute of Energy and Process Systems Engineering Technical University Braunschweig Germany

ISBN: (纸本)9789897583230

Alkaline methanol oxidation is an electrochemical process, perspective for the design of efficient high energy density fuel cells. The process involves a large number of elementary reactions, forming a complex reaction graph, and it is described by a system of non-linear differential equations of high order. The purpose of parameter identification is a reconstruction of reaction constants in this model on the basis of available experimental data. Cyclic voltammetry, a measurement of dynamical current-voltage characteristic of the cell, is especially suitable for analysis of electrochemical kinetics. In this paper we present several approaches for parameter identification in cyclic voltammetry of alkaline methanol oxidation. With the aid of global optimization methods and interactive parameter study we find four islands of solutions in parameter space, corresponding to different chemical mechanisms of the process. The main features of solutions are discussed and the reconstructed reaction constants are presented. Copyright © 2018 by SCITEPRESS-Science and Technology Publications, Lda. All rights reserved.

关键词： Differential equations

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Computational Life Sciences 1

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丛书名： Studies in Big Data

1000年

作者： Jens Dörpinghaus Sebastian Schaaf Vera Weil Alexander Apke

ISBN: (数字)9783031084119

ISBN: (纸本)9783031084102;9783031084133

This book broadly covers the given spectrum of disciplines in Computational Life Sciences, transforming it into a strong helping hand for teachers, students, practitioners and researchers. In Life Sciences, problem-solving and data analysis often depend on biological expertise combined with technical skills in order to generate, manage and efficiently analyse big data. These technical skills can easily be enhanced by good theoretical foundations, developed from well-chosen practical examples and inspiring new strategies. This is the innovative approach of Computational Life Sciences-Data Engineering and Data Mining for Life Sciences: We present basic concepts, advanced topics and emerging technologies, introduce algorithm design and programming principles, address data mining and knowledge discovery as well as applications arising from real projects. Chapters are largely independent and often flanked by illustrative examples and practical advise.

关键词： Data Engineering Bioinformatics Big Data Computational Intelligence

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Sparse tensor product approximation for a class of generalized method of moments estimators

arXiv

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arXiv 2020年

作者： Gilch, Alexandros Griebel, Michael Oettershagen, Jens Institute for Numerical Simulation Bonn Germany Fraunhofer Institute for Algorithms and Scientific Computing SCAI Sankt Augustin Germany

Generalized Method of Moments (GMM) estimators in their various forms, including the popular Maximum Likelihood (ML) estimator, are frequently applied for the evaluation of complex econometric models with not analytically computable moment or likelihood functions. As the objective functions of GMM-and ML-estimators themselves constitute the approximation of an integral, more precisely of the expected value over the real world data space, the question arises whether the approximation of the moment function and the simulation of the entire objective function can be combined. Motivated by the popular Probit and Mixed Logit models, we consider double integrals with a linking function which stems from the considered estimator, e.g. the logarithm for Maximum Likelihood, and apply a sparse tensor product quadrature to reduce the computational effort for the approximation of the combined integral. Given Hölder continuity of the linking function, we prove that this approach can improve the order of the convergence rate of the classical GMM-and ML-estimator by a factor of two, even for integrands of low regularity or high dimensionality. This result is illustrated by numerical simulations of Mixed Logit and Multinomial Probit integrals which are estimated by ML-and GMM-estimators, *** Codes 62P20, 65D30, 65D32 © 2020, CC BY.

关键词： Method of moments

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