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检索条件"主题词=PARALLEL algorithms"

共 8963 条记录，以下是1691-1700 订阅

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Using Random Butterfly Transformations in parallel Schur Complement-Based Preconditioning

Using Random Butterfly Transformations in Parallel Schur Com...

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3rd International Conference on Innovative Network Systems and Applications (iNetSApp) held in conjunction with Federated Conference on Computer Science and Information Systems (FedCSIS)

作者： Baboulin, Marc Jamal, Aygul Sosonkina, Masha Univ Paris 11 Bat 425 F-91405 Orsay France Old Dominion Univ Norfolk VA 23529 USA

ISBN: (纸本)9788360810668

We propose to use a randomization technique based on Random Butterfly Transformations (RBT) in the Algebraic Recursive Multilevel Solver (ARMS) to improve the preconditioning phase in the iterative solution of sparse linear systems. We integrated the RBT technique into the parallel version of ARMS (pARMS). The preliminary experimental results on some matrices from the Davis' collection show an improvement of the convergence and accuracy of the results when compared with existing implementations of the pARMS preconditioner.

关键词： iterative methods matrix algebra parallel algorithms randomised algorithms recursive estimation RBT technique algebraic recursive multilevel solver iterative solution matrices pARMS preconditioner parallel ARMS parallel Schur complement-based preconditioning preconditioning phase improvement random butterfly transformations randomization technique sparse linear systems Accuracy Iterative methods Linear systems Program processors Sparse matrices Symmetric matrices Yttrium iterative methods Linear system iterative solution Program processors Symmetric matrix recursive estimation Sparse matrix matrix algebra parallel algorithms Rare earths yttrium matrices randomized algorithms

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A parallel Tree Grafting Algorithm for Maximum Cardinality Matching in Bipartite Graphs 29

A Parallel Tree Grafting Algorithm for Maximum Cardinality M...

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29th IEEE International parallel and Distributed Processing Symposium (IPDPS)

作者： Azad, Ariful Buluc, Aydin Pothen, Alex Lawrence Berkeley Natl Lab Berkeley CA 94720 USA Purdue Univ W Lafayette IN 47907 USA

ISBN: (纸本)9781479986484

In computing matchings in graphs on parallel processors, it is challenging to achieve high performance because these algorithms rely on searching for paths in the graph, and when these paths become long, there is little concurrency. We present a new algorithm and its shared-memory parallelization for computing maximum cardinality matchings in bipartite graphs. Our algorithm searches for augmenting paths via specialized breadth-first searches (BFS) from multiple source vertices, hence creating more parallelism than single source algorithms. Unfortunately, algorithms that employ multiple-source searches cannot discard a search tree once no augmenting path is discovered from the tree, unlike algorithms that rely on single-source searches. We describe a novel tree-grafting method that eliminates most of the redundant edge traversals resulting from this property of multiple-source searches. We also employ the recent direction-optimizing BFS algorithm as a subroutine to discover augmenting paths faster. Our algorithm compares favorably with the current best algorithms in terms of the number of edges traversed, the average augmenting path length, and the number of iterations. We provide a proof of correctness for our algorithm. Our NUMA-aware implementation is scalable to 80 threads of an Intel multiprocessor. On average, our parallel algorithm runs an order of magnitude faster than the fastest algorithms available. The performance improvement is more significant on graphs with small matching number.

关键词： bipartite graph cardinality matching matching tree grafting Bipartite graph algorithms Tree searching Byways base number Proof of correctness concurrent processor Paths Searches TWO-COMPONENT parallel algorithms

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A parallel Algorithm for Clipping Polygons with improved bounds and A Distributed Overlay Processing System using MPI 15

A Parallel Algorithm for Clipping Polygons with improved bou...

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2015 15th IEEE ACM International Symposium on Cluster Cloud and Grid Computing (CCGrid 2015)

作者： Puri, Satish Prasad, Sushil K. Georgia State Univ Dept Comp Sci Atlanta GA 30303 USA

ISBN: (纸本)9781479980062

Clipping arbitrary polygons is one of the complex operations in computer graphics and computational geometry. It is applied in many fields such as Geographic Information Systems (GIS) and VLSI CAD. We have two significant results to report. Our first result is the effective parallelization of the classic, highly sequential Greiner-Hormann algorithm, which yields the first output-sensitive CREW PRAM algorithm for a pair of simple polygons, and can perform clipping in O(logn) time using O(n + k) processors, where n is the total number of vertices and k is the number of edge intersections. This improves upon our previous clipping algorithm based on the parallelization of Vatti's sweepline algorithm, which requires O(n + k + k') processors to achieve logarithmic time complexity where k' can be O(n(2)) [1]. This also improves upon another O(logn) time algorithm by Karinthi, Srinivas, and Almasi which unlike our algorithm does not handle self-intersecting polygons, is not output-sensitive, and must employ Theta(n(2)) processors to achieve O(logn) time [2]. We also study multi-core and many-core implementations of our parallel Greiner-Hormann algorithm. Our second result is a practical, parallel GIS system, namely MPI-GIS, for polygon overlay processing of two GIS layers containing large number of polygons over a cluster of compute nodes. It employs R-tree for efficient indexing and identification of potentially intersecting set of polygons across two input GIS layers. Spatial data files tend to be large in size (in GBs) and the underlying overlay computation is highly irregular and compute intensive. This system achieves 44X speedup on a 32-node NERSC's CARVER cluster while processing about 600K polygons in two GIS layers within 19 seconds which takes over 13 minutes on state-of-art ArcGIS system.

关键词： CUDA GPU MPI MPI-GIS PRAM algorithm Polygon Clipping Polygon overlay Polygon polygons message passing mannose phosphate isomerase remote procedure calls clipping parallel algorithms geographic information systems Line clipping PROCESSOR Overlay parallelization

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A parallel Algorithm for Electrostatic Interactions Based on Wolf Method Charge-neutral Condition and Modified Cell-linked List Method 5

A Parallel Algorithm for Electrostatic Interactions Based on...

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5th International Conference on Information Science and Technology (ICIST)

作者： Kim, Myongchan Choe, Kwangchol Go, Guangsu Che, Ming Tianjin Univ Sch Comp Sci & Technol Tianjin Peoples R China

ISBN: (纸本)9781479974894

The Wolf method and the Wolf method charge-neutral condition proposed by Yonezawa ensure that electrostatic interactions are short-ranged. In the modified cell-linked list method, the performances of parallel systems increase or decrease by reducing the cell size. Both the multi-cell MD method and the modified cell-linked list method are the effective short-range force parallel computing methods. In this article, we apply these key ideas from both the Wolf method charge-neutral condition and the modified cell-linked list method to the multi-cell MD method, and propose a model and a method for an optimization calculation of electrostatic interactions. The optimization variable is the total number of force calculations, depends on the number of particles, the number of processors, the cutoff radius and the cell size. Results show that our optimization model is correct, that our method using the optimization model and the Wolf method charge-neutral condition ensures the high performance, because it has all the advantages of three methods.

关键词： electrostatic interactions wolf parallel algorithms Cell Size parallel system

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parallel Distributed Memory Construction of Suffix and Longest Common Prefix Arrays 15

Parallel Distributed Memory Construction of Suffix and Longe...

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International Conference for High Performance Computing, Networking, Storage and Analysis (SC)

作者： Flick, Patrick Aluru, Srinivas Georgia Inst Technol Atlanta GA 30332 USA

ISBN: (纸本)9781450337236

Suffix arrays and trees are fundamental string data structures of importance to many applications in computational biology. Consequently, their parallel construction is an actively studied problem. To date, algorithms with best practical performance lack efficient worst-case run-time guarantees, and vice versa. In addition, much of the recent work targeted low core count, shared memory parallelization. In this paper, we present parallel algorithms for distributed memory construction of suffix arrays and longest common prefix (LCP) arrays that simultaneously achieve good worst-case run-time bounds and superior practical performance. Our algorithms run in O(T-sort(n, p). log n) worst-case time where T-sort(n, p) is the run-time of parallel sorting. We present several algorithm engineering techniques that improve performance in practice. We demonstrate the construction of suffix and LCP arrays of the human genome in less than 8 seconds on 1,024 Intel Xeon cores, reaching speedups of over 110X compared to the best sequential suffix array construction implementation divsufsort.

关键词： Arrays Sorting Genomics Bioinformatics Program processors parallel algorithms Silicon benzoylprop-ethyl parallel algorithms Program processors Bioinformatics Suffix Genomics arrays sorting programs Silicon Runtime CASING RUNNING parallel architectures distributed memory Human Genome grade

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parallel Top-k Query Processing on Uncertain Strings Using MapReduce 20th

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20th International Conference on Database Systems for Advanced Applications (DASFAA)

作者： Xu, Hui Ding, Xiaofeng Jin, Hai Jiang, Wenbin Huazhong Univ Sci & Technol Sch Comp Sci & Technol Cluster & Grid Comp Lab Serv Comp Technol & Syst Lab Wuhan 430074 Peoples R China

ISBN: (纸本)9783319181233;9783319181226

Top-k query is an important and essential operator for data analysis over string collections. However, when uncertainty comes into big data, it calls for new parallel algorithms for efficient query processing on large scale uncertain strings. In this paper, we proposed a MapReduce-based parallel algorithm, called MUSK, for answering top-k queries over large scale uncertain strings. We used the probabilistic n-grams to generate key-value pairs. To improve the performance, a novel lower bound for expected edit distance was derived to prune strings based on a new defined function gram mapping distance. By integrating the bound with TA, the filtering power in the Map stage was optimized effectively to decrease the transmission cost. Comprehensive experimental results on both real-world and synthetic datasets showed that MUSK outperformed the baseline approach with speeds up to 6 times in the best case, which indicated good scalability over large datasets.

关键词： parallel algorithms

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On Implementation High-Scalable CFD Solvers for Hybrid Clusters with Massively-parallel Architectures 13th

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13th International Conference on parallel Computing Technologies (PaCT)

作者： Pavlukhin, Pavel Menshov, Igor MV Keldysh Appl Math Inst Moscow 125047 Russia Res & Dev Inst Kvant Moscow 125438 Russia

ISBN: (纸本)9783319219097;9783319219080

New approach for solving of compressible fluid dynamic problems with complex geometry on Cartesian grids is proposed. It leads to algorithmic uniformity for whole domain and structured memory accesses which are essential for effective implementations on massively-parallel architectures - GPUs. Methods used are based on implicit scheme and LU-SGS method. Novel parallel algorithm for last one is proposed. In-depth analysis of CUDA+MPI implementation (interoperability issues, libraries tuning) scalable up to hundreds GPUs is performed.

关键词： CFD CUDA LU-SGS Implicit schemes parallel algorithms

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MEMORY EFFICIENT SPECTRAL ESTIMATION ON parallel COMPUTING ARCHITECTURES

MEMORY EFFICIENT SPECTRAL ESTIMATION ON PARALLEL COMPUTING A...

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IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE)

作者： Barjenbruch, Michael Gritschneder, Franz Dietmayer, Klaus Klappstein, Jens Dickmann, Juergen Univ Ulm Inst Measurement Control & Microtechnol Ulm Germany Daimler AG Dept Environm Percept Ulm Germany

ISBN: (纸本)9781467391696

A method for spectral estimation is proposed. It is based on the multidimensional extensions of the RELAX algorithm. The fast Fourier transform is replaced by multiple Chirp-Z transforms. Each transform has a much shorter length than the transform in the original algorithm. This reduces the memory requirements significantly. At the same time a high degree of parallelism is preserved. A detailed analysis of the computational requirements is given. Finally, the proposed method is applied to automotive radar measurements. It is shown, that the multidimensional spectral estimation resolves multiple scattering centers on an extended object.

关键词： Multidimensional signal processing parameter estimation harmonic analysis parallel algorithms

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SOLVING GENERALIZED VEHICLE ROUTING PROBLEM BY parallel UNIVERSES AND TABU SEARCH 6

SOLVING GENERALIZED VEHICLE ROUTING PROBLEM BY PARALLEL UNIV...

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6th International Conference on Computing, Communication and Networking Technologies (ICCCNT)

作者： Navidadham, Mohammadhossein Arbabsadeghi, Mostafa Bayat, Alireza Akbari Didehvar, Farzad Amirkabir Univ Comp Sci Tehran Iran Univ Tehran Comp Sci Tehran 14174 Iran

ISBN: (纸本)9781479979837

Vehicle routing problem (VRP) is one of the most important transportation problems in such a way that most of the transportation problems are changeable to it. This problem can be considerably effective in transportation and the costs arising from it. The VRP with some constraints and limitations become closer to the actual world. The generalized problem of VRP is in a state that should select agents among the customers so that the problem to be solved in a more generalized form. In this paper, we have tried to improve the answers on generalized vehicle routing transportation problems (GVRP) and obtain a better result in implementation, using the combination of parallel universes' algorithms in addition to the Tabu search. Our results indicate that our method has been productive successful and we have achieved better answers compared to the similar algorithms presented until now, in this context.

关键词： transportation heuristic algorithms parallel algorithms optimization Shortest path problem

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A Work-Efficient Algorithm for parallel Unordered Depth-First Search 15

A Work-Efficient Algorithm for Parallel Unordered Depth-Firs...

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International Conference for High Performance Computing, Networking, Storage and Analysis (SC)

作者： Acar, Umut A. Chargueraud, Arthur Rainey, Mike Carnegie Mellon Univ Pittsburgh PA 15213 USA Inria Rocquencourt France LRI Univ Paris Sud CNRS Gif Sur Yvette France

ISBN: (纸本)9781450337236

Advances in processing power and memory technology have made multicore computers an important platform for high-performance graph-search (or graph-traversal) algorithms. Since the introduction of multicore, much progress has been made to improve parallel breadth-first search. However, less attention has been given to algorithms for unordered or loosely ordered traversals. We present a parallel algorithm for unordered depth-first-search on graphs. We prove that the algorithm is work efficient in a realistic algorithmic model that accounts for important scheduling costs. This work-efficiency result applies to all graphs, including those with high diameter and high out-degree vertices. The algorithmic techniques behind this result include a new data structure for representing the frontier of vertices in depth-first search, a new amortization technique for controlling excess parallelism, and an adaptation of the lazy-splitting technique to depth first search. We validate the theoretical results with an implementation and experiments. The experiments show that the algorithm performs well on a range of graphs and that it can lead to significant improvements over comparable algorithms.

关键词： A Work-Efficient Algorithm parallel Unordered Depth-First Search important scheduling costs Depth--first search Unordered Multi-core processors algorithms processing power parallel algorithms new data

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