检索结果-内蒙古大学图书馆

作者： Jakub TARNAWSKI ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE

学位级别：博士

In this thesis we give new algorithms for two fundamental graph problems. We develop novel ways of using linear programming formulations, even exponential-sized ones, to extract structure from problem instances and to guide algorithms in making progress. Somewhat surprisingly, similar polyhedral techniques can be harnessed in the two seemingly disparate settings. In the first part of the thesis we address a benchmark problem in combinatorial optimization: the asymmetric traveling salesman problem (ATSP). It consists in finding the shortest tour that visits all vertices of a given directed graph with weights on edges. Due to its NP-hardness, the theoretical study of algorithms for ATSP has focused on approximation algorithms: ones that are provably both efficient and give solutions competitive with the optimum. Specifically, a ρ-approximation algorithm for ATSP is one that runs in polynomial time and always outputs a tour that is at most ρ times longer than the shortest tour. Finding such an approximation algorithm with ρ bounded (i. e., a constant factor) had been a long-standing open problem. In this thesis, we give such an algorithm. Our approximation guarantee is analyzed with re- spect to the standard linear programming relaxation, and thus our result also confirms the conjec- tured constant integrality gap of that relaxation. Our techniques build upon the constant-factor approximation algorithm for the special case of node-weighted metrics due to Svensson [Sve15]. In particular, we give a generic reduction to structured instances that resemble but are more general than those arising from node-weighted metrics. This reduction takes advantage of a laminar family of vertex sets that arises from the linear programming relaxation. In the second part of the thesis we address the perfect matching problem. The first polynomial- time algorithm for it, given by Edmonds in 1965 [Edm65b], is historically associated with the in- troduction of the class P and our notion that

关键词： graph algorithms linear programming traveling salesman problem perfect matching derandomization parallel algorithms approximation algorithms combinatorial optimization discrete optimization theoretical computer science

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parallel algorithms for Counting Triangles and Computing Clustering Coefficients

Parallel Algorithms for Counting Triangles and Computing Clu...

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25th ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis (SC)

作者： Arifuzzaman, S. M. Khan, Maleq Marathe, Madhav V. Virginia Tech Dept Comp Sci Blacksburg VA 24061 USA Virginia Tech Virginia Bioinformat Inst Blacksburg VA 24061 USA

ISBN: (纸本)9780769549569;9781467362184

We present MPI-based parallel algorithms for counting triangles and computing clustering coefficients in massive networks. Counting triangles is important in the analysis of various networks, e.g., social, biological, web etc. Emerging massive networks do not fit in the main memory of a single machine and are very challenging to work with. Our distributed-memory parallel algorithm allows us to deal with such massive networks in a time- and space-efficient manner. We were able to count triangles in a graph with 2 billions of nodes and 50 billions of edges in 10 minutes. Our parallel algorithm for computing clustering coefficients uses efficient external memory aggregation. We also show how edge sparsification technique can be used with our parallel algorithm to find approximate number of triangles without sacrificing the accuracy of estimation. In addition, we propose a simple modification of a state-of - The-art sequential algorithm that improves both runtime and space requirement. © 2012 IEEE.

关键词： Clustering Coefficients HPC Massive Graphs parallel algorithms Triangles

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Communication lower-bounds for distributed-memory computations for mass spectrometry based omics data

arXiv

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arXiv 2020年

作者： Saeed, Fahad Haseeb, Muhammad Iyengar, Ss MiamiFL33199 United States

Mass spectrometry (MS) based omics data analysis require significant time and resources. To date, few parallel algorithms have been proposed for deducing peptides from mass spectrometry-based data. However, these parallel algorithms were designed, and developed when the amount of data that needed to be processed was smaller in scale. In this paper, we prove that the communication bound that is reached by the existing parallel algorithms is Ω(mn + 2r pq ), where m and n are the dimensions of the theoretical database matrix, q and r are dimensions of spectra, and p is the number of processors. We further prove that communication-optimal strategy with fast-memory √M = mn + 2qr can achieve Ω(2mnqp ) but is not achieved by any existing parallel p proteomics algorithms till date. To validate our claim, we performed a meta-analysis of published parallel algorithms, and their performance results. We show that suboptimal speedups with increasing number of processors is a direct consequence of not achieving the communication lower-bounds. We further validate our claim by performing experiments which demonstrate the communication bounds that are proved in this paper. Consequently, we assert that next-generation of provable, and demonstrated superior parallel algorithms are urgently needed for MS based large systems-biology studies especially for meta-proteomics, proteogenomic, microbiome, and proteomics for non-model organisms. Our hope is that this paper will excite the parallel computing community to further investigate parallel algorithms for highly influential MS based omics problems. Copyright © 2020, The Authors. All rights reserved.

关键词： parallel algorithms

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Fast random cactus graph generation 9th

Fast random cactus graph generation

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9th International Conference on Supercomputing, ISUM 2018

作者： Trejo-Sánchez, Joel Antonio Vela-Navarro, Andrés Flores-Lamas, Alejandro López-Martínez, José Luis Bermejo-Sabbagh, Carlos Cuevas-Cuevas, Nora Leticia Toral-Cruz, Homero CONACyT-Centro de Investigación en Matemáticas Sierra PapacalYucatán Mexico Tecnológico Nacional de México-I.T. Mérida Periférico Poniente Mérida Mérida Mexico Centro de Investigación Científica y de Educación Superior de Ensenada Baja California Mexico Universidad Autónoma de Yucatán TizimínYucatán Mexico Universidad de Quintana Roo ChetumalQuintana Roo Mexico

ISBN: (纸本)9783030104474

In this article, we propose a fast algorithm for generating a cactus graph. Cacti has important applications in diverse areas such as biotechnology, telecommunication systems, sensor networks, among others. Thus, generating good random cacti graphs it is important for simulation of the diverse algorithms and protocols. In this paper, we present an efficient parallel algorithm to generate random cactus. To the best of our knowledge, this algorithm is the first parallel algorithm to generate random cacti graphs. © Springer Nature Switzerland AG 2019.

关键词： parallel algorithms

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High-Performance Computing and Engineering Educational Development and Practice

High-Performance Computing and Engineering Educational Devel...

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Frontiers in Education (FIE) Conference

作者： Juan Chen John Impagliazzo Li Shen College of Computer National University of Defense Technology Changsha China School of Engineering and Applied Science Hofstra University New York USA

ISBN: (数字)9781728189611

ISBN: (纸本)9781728189628

This Innovate Practice Full Paper presents HPC and engineering educational development and practice. Educators and researchers are witnessing the emergence of parallel and high-performance computing (HPC) in many computing and engineering environments worldwide. Single-core processing is slowly becoming obsolete while parallel solutions to application development are now replacing serial solutions to achieve higher performance, particularly in many scientific, engineering, and computing fields. Some universities or research institutes worldwide have developed and have become centers of supercomputing. Most of these centers, particularly the world acclaimed Tianhe-2 supercomputer developed by China's National University of Defense Technology (NUDT), often have their own HPC educational approaches as well as their own curricula at both undergraduate and graduate levels. This paper presents some high-level HPC educational concepts, educational framework designs, and strategies for cultivating HPC talented graduates. In this work, the authors show unique perspectives and practical experiences on student capability, oriented toward HPC curricular development. They also show a step-by-step practical system in which real platform, real application, and research-teaching integration modes can immerse students into an HPC world for better understanding. The authors show how researchers with rich computing and engineering experience can become deeply involved in course design, in-class teaching, and in laboratory instruction. They also discuss the effectiveness of HPC courses at the NUDT and they show how HPC can become a stable element in computing and engineering education.

关键词： Education Computational modeling Supercomputers Complexity theory parallel algorithms Maintenance engineering Knowledge engineering

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GPU parallel Visibility Algorithm for a Set of Segments Using Merge Path

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Electronic Notes in Theoretical Computer Science 2019年 342卷 57-69页

作者： Kevin Zúñiga Gárate Escuela Profesional de Ingeniería de Sistemas Universidad Nacional de San Agustín Arequipa Peru

In this paper, we present an efficient parallel algorithm for computing the visibility region for a point in a plane among a non-intersecting set of segments. The algorithm is based on the cascading divide-and-conquer technique and uses merge path to evenly distribute the workload between processors. We implemented the algorithm on NVIDIA's CUDA platform where it performed with a speedup up to 76x with respect to the serial CPU version.

关键词： computational geometry visibility gpu nvidia cuda parallel algorithms mergesort divide and conquer

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parallel algorithms for Tensor Product-based Inexact Graph Matching

Parallel Algorithms for Tensor Product-based Inexact Graph M...

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International Joint Conference on Neural Networks (IJCNN)

作者： Livi, Lorenzo Rizzi, Antonello Univ Roma La Sapienza Dept Informat Engn Elect & Telecommun I-00184 Rome Italy

ISBN: (纸本)9781467314909

In this paper we face the inexact graph matching problem from the parallel algorithms viewpoint. After a brief introduction of both graph matching and parallel computing contexts, we discuss a specific method of performing inexact graph matching based on the well known tensor product operator. We analyze the problem using two parallel computing models, following different algorithmic strategies, and performing also an experimental evaluation. The aim of this paper is to provide modeling and algorithmic strategies to extend inexact graph matching methods to graphs of high order and size, conceiving the computational problem in the more wider context of graph-based Pattern Recognition and Soft Computing systems. As a whole, the obtained results encourage more effort on this direction.

关键词： parallel algorithms

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A scalable graph generation algorithm to sample over a given shell distribution

A scalable graph generation algorithm to sample over a given...

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IEEE International Symposium on parallel and Distributed Processing Workshops and Phd Forum (IPDPSW)

作者： M. Yusuf Özkaya M. Fatih Balin Ali Pinar Ümit V. Çatalyürek School of Computational Science and Engineeering Georgia Institute of Technology Atlanta GA USA Sandia National Laboratories Livermore CA USA

ISBN: (数字)9781728174457

ISBN: (纸本)9781728174570

Graphs are commonly used to model the relationships between various entities. These graphs can be enormously large and thus, scalable graph analysis has been the subject of many research efforts. To enable scalable analytics, many researchers have focused on generating realistic graphs that support controlled experiments for understanding how algorithms perform under changing graph features. Significant progress has been made on scalable graph generation which preserve some important graph properties (e.g., degree distribution, clustering coefficients). In this paper, we study how to sample a graph from the space of graphs with a given shell distribution. Shell distribution is related to the k-core, which is the largest subgraph where each vertex is connected to at least k other vertices. A k-shell is the subset of vertices that are in k-core but not (k + 1)-core, and the shell distribution comprises the sizes of these shells. Core decompositions are widely used to extract information from graphs and to assist other computations. We present a scalable shared and distributed memory graph generator that, given a shell decomposition, generates a random graph that conforms to it. Our extensive experimental results show the efficiency and scalability of our methods. Our algorithm generates 233 vertices and 237 edges in less than 50 seconds on 384 cores.

关键词： Generators Histograms Laboratories parallel algorithms Partitioning algorithms Indexes Software algorithms

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GPU-Accelerated Computation of Vietoris-Rips Persistence Barcodes

arXiv

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arXiv 2020年

作者： Zhang, Simon Xiao, Mengbai Wang, Hao

The computation of Vietoris-Rips persistence barcodes is both execution-intensive and memory-intensive. In this paper, we study the computational structure of Vietoris-Rips persistence barcodes, and identify several unique mathematical properties and algorithmic opportunities with connections to the GPU. Mathematically and empirically, we look into the properties of apparent pairs, which are independently identifiable persistence pairs comprising up to 99% of persistence pairs. We give theoretical upper and lower bounds of the apparent pair rate and model the average case. We also design massively parallel algorithms to take advantage of the very large number of simplices that can be processed independently of each other. Having identified these opportunities, we develop a GPU-accelerated software for computing Vietoris-Rips persistence barcodes, called Ripser++. The software achieves up to 30x speedup over the total execution time of the original Ripser and also reduces CPU-memory usage by up to 2.0x. We believe our GPU-acceleration based efforts open a new chapter for the advancement of topological data analysis in the post-Moore’s Law era. Copyright © 2020, The Authors. All rights reserved.

关键词： parallel algorithms

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On the Direct Kinematics Problem of parallel Mechanisms

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JOURNAL OF ROBOTICS 2018年第3-12期2018卷 1-9页

作者： Seibel, Arthur Schulz, Stefan Schlattmann, Josef Hamburg Univ Technol Workgrp Syst Technol & Engn Design Methodol D-21073 Hamburg Germany

The direct kinematics problem of parallel mechanisms, that is, determining the pose of the manipulator platform from the linear actuators' lengths, is, in general, uniquely not solvable. For this reason, instead of measuring the lengths of the linear actuators, we propose measuring their orientations and, inmost cases, also the orientation of the manipulator platform. This allows the design of a low-cost sensor system for parallel mechanisms that completely renounces length measurements and provides a unique solution of their direct kinematics.

关键词： Actuators Kinematics parallel algorithms Automatic control Linear accelerators

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