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检索条件"主题词=PARALLEL algorithms"

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A parallel Algorithm for Finding All Pairs κ-Mismatch Maximal Common Substrings

A Parallel Algorithm for Finding All Pairs κ-Mismatch Maxim...

引用

Supercomputing Conference

作者： Sriram P. Chockalingam Sharma V. Thankachan Srinivas Aluru Dept. of Computer Science and Engineering Indian Institute of Technology Mumbai India School of Computational Science and Engineering Georgia Institute of Technology Atlanta USA

ISBN: (纸本)9781467388160

We present an efficient parallel algorithm for the following problem: Given an input collection D of n sequences of total length N, a length threshold f and a mismatch threshold κ, report all κ-mismatch maximal common substrings of length at least f over all pairs of strings in D. This problem is motivated by clustering and assembly applications in computational biology, where D is a collection of millions of short DNA sequences. Sequencing errors and massive size of these datasets necessitate efficient parallel approximate sequence matching algorithms. We present a novel distributed memory parallel algorithm that solves this approximate sequence matching problem in O ((N/p log N + occ)log k N) expected time and takes only O(log k+1 N) expected rounds of global communications, under some realistic assumptions, where p is the number of processors and occ is the output size. To our knowledge, this is the first provably sub-quadratic time algorithm for solving this problem. We demonstrate the performance and scalability of our algorithm using large high throughput sequencing data sets.

关键词： Program processors parallel algorithms Arrays Sequential analysis Electronic mail Clustering algorithms

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On Speeding-up parallel Jacobi Iterations for SVDs

On Speeding-up Parallel Jacobi Iterations for SVDs

引用

IEEE International Conference on High Performance Computing and Communications

作者： Soumitra Pal Sudipta Pathak Sanguthevar Rajasekaran Computer Science and Engineering University of Connecticut 371 Fairfield Road Storrs CT 06269 USA

ISBN: (纸本)9781509042982

We live in an era of big data and the analysis of these data is becoming a bottleneck in many domains including biology and the internet. To make these analyses feasible in practice, we need efficient data reduction algorithms. The Singular Value Decomposition (SVD) is a data reduction technique that has been used in many different applications. For example, SVDs have been extensively used in text analysis. The best known sequential algorithms for the computation of SVDs take cubic time which may not be acceptable in practice. As a result, many parallel algorithms have been proposed in the literature. There are two kinds of algorithms for SVD, namely, QR decomposition and Jacobi iterations. Researchers have found out that even though QR is sequentially faster than Jacobi iterations, QR is difficult to parallelize. As a result, most of the parallel algorithms in the literature are based on Jacobi iterations. For example, the Jacobi Relaxation Scheme (JRS) of the classical Jacobi algorithm has been shown to be very effective in parallel. In this paper we propose a novel variant of the classical Jacobi algorithm that is more efficient than the JRS algorithm. Our experimental results confirm this assertion. The key idea behind our algorithm is to select the pivot elements for each sweep appropriately. We also show how to efficiently implement our algorithm on such parallel models as the PRAM and the mesh.

关键词： SVD Jacobi iterations JRS parallel algorithms

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Efficient parallel Ear Decomposition of Graphs with Application to Betweenness-Centrality

Efficient Parallel Ear Decomposition of Graphs with Applicat...

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International Conference on High Performance Computing

作者： Charudatt Pachorkar Meher Chaitanya Kishore Kothapalli Debajyoti Bera International Institute of Information Technology Hyderabad Hyderabad India Delhi Okhla Industrial Estate Indraprastha Institute of Information Technology New Delhi India

ISBN: (纸本)9781509054121

parallel graph algorithms continue to attract a lot of research attention given their applications to several fields of sciences and engineering. Efficient design and implementation of graph algorithms on modern manycore accelerators has to however contend with a host of challenges including not being able to reach full memory system throughput and irregularity. Of late, focusing on real-world graphs, researchers are addressing these challenges by using decomposition and preprocessing techniques guided by the structural properties of such graphs. In this direction, we present a new GPU algorithm for obtaining an ear decomposition of a graph. Our implementation of the proposed algorithm on an NVidia Tesla K40c improves the state-of-the-art by a factor of 2.3x on average on a collection of real-world and synthetic graphs. The improved performance of our algorithm is due to our proposed characterization that identifies edges of the graph as redundant for the purposes of an ear decomposition. We then study an application of the ear decomposition of a graph in computing the betweenness-centrality values of nodes in the graph. We use an ear decomposition of the input graph to systematically remove nodes of degree two. The actual computation of betweenness-centrality is done on the remaining nodes and the results are extended to nodes removed in the previous step. We show that this approach improves the state-of-the-art for computing betweenness-centrality on an NVidia K40c GPU by a factor of 1.9x on average over a collection of real-world graphs.

关键词： Ear Algorithm design and analysis Graphics processing units Partitioning algorithms parallel algorithms Vegetation Information technology

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Online-Autotuning of parallel SAH kD-Trees

Online-Autotuning of Parallel SAH kD-Trees

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International Symposium on parallel and Distributed Processing (IPDPS)

作者： Martin Tillmann Philip Pfaffe Christopher Kaag Walter F. Tichy Institute of Program Structures & Data Organization Karlsruhe Institute of Technology Karlsruhe Germany

ISBN: (纸本)9781509021413

We explore the benefits of using online-autotuning to find an optimal configuration for the parallel construction of Surface Area Heuristic (SAH) kD-trees. Using a quickly converging autotuning mechanism, we achieve a significant performance improvement of up to 1.96x. The SAH kD-tree is a spatial data structure and a fundamental tool in the domain of computer graphics and simulations. The parallel construction of these trees is influenced by several parameters, controlling various aspects of the algorithm. However, the parameter configurations advocated in the literature are hardly ever portable. To boost portability, we apply online-autotuning to four state-of-the-art variants of parallel kD-tree construction. We show that speedups over the variants' standard configurations are possible with low programmer effort. We further demonstrate the performance portability of our approach by evaluating performance on varying multicore platforms and both static and dynamic geometries.

关键词： Tuning Data structures Ray tracing Geometry Hardware parallel algorithms Rendering (computer graphics)

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Improving parallel modularization algorithm of large complex fault trees

Improving parallel modularization algorithm of large complex...

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Annual Symposium on Reliability and Maintainability (RAMS)

作者： Zhifeng Li Yi Ren Linlin Liu Zili Wang Beihang University Beijing China

ISBN: (纸本)9781509002504

Modularization is a significant way to ease the challenge of evaluating large-scale fault trees known as a NP-hard problem, especially for BDD algorithm. In our previous work, we proposed an effective parallel modularization algorithm for large-scale coherent fault trees which only include gates with AND logic and OR logic. But in real engineering scenarios, fault trees usually consist of many complex static logic gates (i.e. K out of N gate, NOT gate, etc.) and dynamic logic gates (i.e. sequence gate, functional dependency gate, etc.). To address these issues, we improve the parallel modularization algorithm and discover its feasibility to confront all sorts of fault trees. Generally, K out of N gate is usually transformed into the combination of AND gates and OR gates, but that will significant increase the scale of the tree and consume more computation resources. As a solution, we treat the K out of N gate as a single module which could be encoded by BDD directly, and then the scale of entire fault tree could be controlled. Besides, we take the non-coherent fault tree and dynamic fault tree into account and find that these complicated logic gates can be regarded as modules too. We can draw the conclusion that our algorithm can be applied to all sorts of fault trees. Moreover, a detailed improvement of the algorithm is that we only start the algorithm from the bottom events with more than one outgoing edges, and that means we need not to traverse all nodes of the large fault tree. It is meaningful to save the computation resources. In the experiment section, we compare computation time of the improving algorithm with our previous works. And illustrates that the superiority of the improving algorithm through some graphs in various aspects.

关键词： Fault trees Logic gates parallel algorithms Heuristic algorithms Algorithm design and analysis Data structures Boolean functions

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Communication-Avoiding parallel Sparse-Dense Matrix-Matrix Multiplication

Communication-Avoiding Parallel Sparse-Dense Matrix-Matrix M...

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International Symposium on parallel and Distributed Processing (IPDPS)

作者： Penporn Koanantakool Ariful Azad Aydin Buluç Dmitriy Morozov Sang-Yun Oh Leonid Oliker Katherine Yelick Computational Research Division Lawrence Berkeley National Laboratory Berkeley USA EECS Department University of California Berkeley USA Department of Statistics and Applied Probability University of California Santa Barbara USA

ISBN: (纸本)9781509021413

Multiplication of a sparse matrix with a dense matrix is a building block of an increasing number of applications in many areas such as machine learning and graph algorithms. However, most previous work on parallel matrix multiplication considered only both dense or both sparse matrix operands. This paper analyzes the communication lower bounds and compares the communication costs of various classic parallel algorithms in the context of sparse-dense matrix-matrix multiplication. We also present new communication-avoiding algorithms based on a 1D decomposition, called 1.5D, which - while suboptimal in dense-dense and sparse-sparse cases - outperform the 2D and 3D variants both theoretically and in practice for sparse-dense multiplication. Our analysis separates one-time costs from per iteration costs in an iterative machine learning context. Experiments demonstrate speedups up to 100x over a baseline 3D SUMMA implementation and show parallel scaling over 10 thousand cores.

关键词： Sparse matrices Three-dimensional displays Partitioning algorithms Algorithm design and analysis Machine learning algorithms parallel algorithms Covariance matrices

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20 Years of Teaching parallel Processing to Computer Science Seniors

20 Years of Teaching Parallel Processing to Computer Science...

引用

Workshop on Education for High Performance Computing (EduHPC)

作者： Jie Liu Computer Science Division Western Oregon University Monmouth Oregon USA

In this paper, we present our Concurrent Systems class, where parallel programming and parallel and distributed computing (PDC) concepts have been taught for more than 20 years. Despite several rounds of changes in hardware, the class maintains its goals of allowing students to learn parallel computer organizations, studying parallel algorithms, and writing code to be able to run on parallel and distributed platforms. We discuss the benefits of such a class, reveal the key elements in developing this class and receiving funding to replace outdated hardware. We will also share our activities in attracting more students to be interested in PDC and related topics.

关键词： Computers parallel programming parallel algorithms Hardware Education

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A General Purpose Branch and Bound parallel Algorithm

A General Purpose Branch and Bound Parallel Algorithm

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Euromicro Conference on parallel, Distributed and Network-Based Processing

作者： Alexandros C. Dimopoulos Christos Pavlatos George Papakonstantinou Harokopio University of Athens Tavros Greece Hellenic Air Force Academy Athens Greece National Technical University of Athens Zografou Greece

In this paper a parallel algorithm for branch and bound applications is proposed. The algorithm is a general purpose one and it can be used to parallelize effortlessly any sequential branch and bound style algorithm, that is written in a certain format. It is a distributed dynamic scheduling algorithm, i.e. each node schedules the load of its cores, it can be used with different programming platforms and architectures and is a hybrid algorithm (OpenMP, MPI). To prove its validity and efficiency the proposed algorithm has been implemented and tested with numerous examples in this paper that are described in detail. A speed-up of about 9 has been achieved for the tested examples, for a cluster of three nodes with four cores each.

关键词： Instruction sets Clustering algorithms Arrays Heuristic algorithms Partitioning algorithms parallel algorithms

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parallel Experiments with RARE-BLAS

Parallel Experiments with RARE-BLAS

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International Symposium on Symbolic and Numeric algorithms for Scientific Computing (SYNASC)

作者： Chemseddine Chohra Philippe Langlois David Parello DALI Laboratoire d'Informatique Robotique et de Microélectronique de Montpellier Montpellier CNRS France

ISBN: (纸本)9781509057085

Numerical reproducibility failures rise in parallel computation because of the non-associativity of floating-point summation. Optimizations on massively parallel systems dynamically modify the floating-point operation order. Hence, numerical results may change from one run to another. We propose to ensure reproducibility by extending as far as possible the IEEE-754 correct rounding property to larger operation sequences. Our RARE-BLAS (Reproducible, Accurately Rounded and Efficient BLAS) benefits from recent accurate and efficient summation algorithms. Solutions for level 1 (asum, dot and nrm2) and level 2 (gemv) routines are provided. We compare their performance to the Intel MKL library and to other existing reproducible algorithms. For both shared and distributed memory parallel systems, we exhibit an extra-cost of 2× in the worst case scenario, which is satisfying for a wide range of applications. For Intel Xeon Phi accelerator a larger extra-cost (4× to 6×) is observed, which is still helpful at least for debugging and validation.

关键词： Sockets Instruction sets Libraries Bandwidth Scalability Debugging parallel algorithms

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Fast parallel Operations on Search Trees

Fast Parallel Operations on Search Trees

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International Conference on High Performance Computing

作者： Yaroslav Akhremtsev Peter Sanders KIT Institute of Theoretical Informatics Karlsruhe Germany

ISBN: (纸本)9781509054121

Using (a, b)-trees as an example, we show how to perform a parallel split with logarithmic latency and parallel join, bulk updates, intersection, union (or merge), and (symmetric) set difference with logarithmic latency and with information theoretically optimal work. We present both asymptotically optimal solutions and simplified versions that perform well in practice - they are several times faster than previous implementations.

关键词： Vegetation Data structures Phase change random access memory Fuses Informatics Electronic mail parallel algorithms

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