408 research outputs found

    Parallel sparse matrix-vector multiplication as a test case for hybrid MPI+OpenMP programming

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    We evaluate optimized parallel sparse matrix-vector operations for two representative application areas on widespread multicore-based cluster configurations. First the single-socket baseline performance is analyzed and modeled with respect to basic architectural properties of standard multicore chips. Going beyond the single node, parallel sparse matrix-vector operations often suffer from an unfavorable communication to computation ratio. Starting from the observation that nonblocking MPI is not able to hide communication cost using standard MPI implementations, we demonstrate that explicit overlap of communication and computation can be achieved by using a dedicated communication thread, which may run on a virtual core. We compare our approach to pure MPI and the widely used "vector-like" hybrid programming strategy.Comment: 12 pages, 6 figure

    Hybrid-parallel sparse matrix-vector multiplication with explicit communication overlap on current multicore-based systems

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    We evaluate optimized parallel sparse matrix-vector operations for several representative application areas on widespread multicore-based cluster configurations. First the single-socket baseline performance is analyzed and modeled with respect to basic architectural properties of standard multicore chips. Beyond the single node, the performance of parallel sparse matrix-vector operations is often limited by communication overhead. Starting from the observation that nonblocking MPI is not able to hide communication cost using standard MPI implementations, we demonstrate that explicit overlap of communication and computation can be achieved by using a dedicated communication thread, which may run on a virtual core. Moreover we identify performance benefits of hybrid MPI/OpenMP programming due to improved load balancing even without explicit communication overlap. We compare performance results for pure MPI, the widely used "vector-like" hybrid programming strategies, and explicit overlap on a modern multicore-based cluster and a Cray XE6 system.Comment: 16 pages, 10 figure

    Order picking with multiple pickers and due dates: Simultaneous solution of order batching, batch assignment and sequencing, and picker routing problems

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    In manual picker-to-parts order picking systems of the kind considered in this article, human operators (order pickers) walk or ride through the warehouse, retrieving items from their storage location in order to satisfy a given demand specified by customer orders. Each customer order is characterized by a certain due date until which all requested items included in the order are to be retrieved and brought to the depot. For the actual picking process, customer orders may be grouped (batched) into more substantial picking orders (batches). The items of a picking order are then collected on a picker tour through the warehouse. Thus, the picking process of each customer order in the batch is only completed when the picker returns to the depot after the last item of the batch has been picked. Whether and to which extend due dates are violated (tardiness) depends on how the customer orders are batched, how the batches are assigned to order pickers, how the assigned batches are sequenced and how the pickers are routed through the warehouse. Existing literature has only treated special aspects of this problem (i.e. the batching problem or the routing problem) so far. In this paper, for the first time, an approach is proposed which considers all aspects simultaneously. A mathematical model of the problem is introduced that allows for solving small problem instances in reasonable computing times. For larger instances, a variable neighborhood descent (VND) algorithm is presented which includes various neighborhood structures regarding the batching and sequencing problem. Furthermore, two sophisticated routing algorithms are integrated into the VND algorithm. By means of numerical experiments, it is shown that this algorithm provides solutions of excellent quality

    Integrated Order Picking and Vehicle Routing with Due Dates

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    Supermarkets typically order their goods from a centrally located distribution center (warehouse). Each order that the warehouse receives is characterized by the requested items, the location of the respective supermarket and a due date by which the items have to be delivered. For processing an order, a human operator (order picker) retrieves the requested items from their storage locations in the warehouse first. The items are then available for shipment and loaded on the vehicle which performs the tour including the respective location of the supermarket. Whether and to which extent a due date is violated (tardiness) depends on the composition of the tours, the corresponding routes and the start dates of the tours (vehicle routing subproblem). The start date of a tour, however, is also affected by the assignment of orders to pickers and the sequence according to which the orders are processed by the pickers (order picking subproblem). Although both subproblems are closely interconnected, they have not been considered simultaneously in the literature so far. In this paper, an iterated local search algorithm is designed for the simultaneous solution of the subproblems. By means of extensive numerical experiments, it is shown that the proposed approach is able to generate high-quality solutions even for large instances. Furthermore, the economic benefits of an integrated solution are investigated. Problem classes are identified, where the sequential solution of the subproblems leads to acceptable results, and it is pointed out in which cases an integrated solution is inevitable

    Peroxidase gene discovery from the horseradish transcriptome

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    BACKGROUND: Horseradish peroxidases (HRPs) from Armoracia rusticana have long been utilized as reporters in various diagnostic assays and histochemical stainings. Regardless of their increasing importance in the field of life sciences and suggested uses in medical applications, chemical synthesis and other industrial applications, the HRP isoenzymes, their substrate specificities and enzymatic properties are poorly characterized. Due to lacking sequence information of natural isoenzymes and the low levels of HRP expression in heterologous hosts, commercially available HRP is still extracted as a mixture of isoenzymes from the roots of A. rusticana. RESULTS: In this study, a normalized, size-selected A. rusticana transcriptome library was sequenced using 454 Titanium technology. The resulting reads were assembled into 14871 isotigs with an average length of 1133 bp. Sequence databases, ORF finding and ORF characterization were utilized to identify peroxidase genes from the 14871 isotigs generated by de novo assembly. The sequences were manually reviewed and verified with Sanger sequencing of PCR amplified genomic fragments, resulting in the discovery of 28 secretory peroxidases, 23 of them previously unknown. A total of 22 isoenzymes including allelic variants were successfully expressed in Pichia pastoris and showed peroxidase activity with at least one of the substrates tested, thus enabling their development into commercial pure isoenzymes. CONCLUSIONS: This study demonstrates that transcriptome sequencing combined with sequence motif search is a powerful concept for the discovery and quick supply of new enzymes and isoenzymes from any plant or other eukaryotic organisms. Identification and manual verification of the sequences of 28 HRP isoenzymes do not only contribute a set of peroxidases for industrial, biological and biomedical applications, but also provide valuable information on the reliability of the approach in identifying and characterizing a large group of isoenzymes

    Numerical approaches to time evolution of complex quantum systems

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    We examine several numerical techniques for the calculation of the dynamics of quantum systems. In particular, we single out an iterative method which is based on expanding the time evolution operator into a finite series of Chebyshev polynomials. The Chebyshev approach benefits from two advantages over the standard time-integration Crank-Nicholson scheme: speedup and efficiency. Potential competitors are semiclassical methods such as the Wigner-Moyal or quantum tomographic approaches. We outline the basic concepts of these techniques and benchmark their performance against the Chebyshev approach by monitoring the time evolution of a Gaussian wave packet in restricted one-dimensional (1D) geometries. Thereby the focus is on tunnelling processes and the motion in anharmonic potentials. Finally we apply the prominent Chebyshev technique to two highly non-trivial problems of current interest: (i) the injection of a particle in a disordered 2D graphene nanoribbon and (ii) the spatiotemporal evolution of polaron states in finite quantum systems. Here, depending on the disorder/electron-phonon coupling strength and the device dimensions, we observe transmission or localisation of the matter wave.Comment: 8 pages, 3 figure

    The Groundwater Drought Initiative (GDI): analysing and understanding groundwater drought across Europe

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    In Europe, it is estimated that around 65 % of drinking water is extracted from groundwater. Worryingly, groundwater drought events (defined as below normal groundwater levels) pose a threat to water security. Groundwater droughts are caused by seasonal to multi-seasonal or even multi-annual episodes of meteorological drought during which the drought propagates through the river catchment into the groundwater system by mechanisms of pooling, lagging, and lengthening of the drought signals. Recent European drought events in 2010–2012, 2015 and 2017–2018 exhibited spatial coherence across large areas, thus demonstrating the need for transboundary monitoring and analysis of groundwater level fluctuations. However, such monitoring and analysis of groundwater drought at a pan-European scale is currently lacking, and so represents a gap in drought research as well as in water management capability. To address this gap, the European Groundwater Drought Initiative (GDI), a pan-European collaboration, is undertaking a large-scale data synthesis of European groundwater level data. This is being facilitated by the establishment of a new network to co-ordinate groundwater drought research across Europe. This research will deliver the first assessment of spatio-temporal changes in groundwater drought status from ∼1960 to present, and a series of case studies on groundwater drought impacts in selected temperate and semi-arid environments across Europe. Here, we describe the methods used to undertake the continental-scale status assessment, which are more widely applicable to transboundary or large-scale groundwater level analyses also in regions beyond Europe, thereby enhancing groundwater management decisions and securing water supply
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