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9th Asia-Pacific Computer Systems Architecture Conference (ACSAC 2004)

作者： Wu, YF Xu, YL Chen, GL Univ Sci & Technol China Natl High Performance Comp Ctr Hefei Dept Comp Sci & Technol Hefei 230027 Peoples R China

Steiner connected dominating set (SCDS) is a generalization of the famous connected dominating set problem, where only a specified set of required vertices has to be dominated by a connected dominating set, and known to be NP-hard. This paper firstly modifies the SCDS algorithm of Guha and Khuller and achieves a worst case approximation ratio of (2 + 1/(m - 1))H(min(Delta, k)) + O(1), which outperforms the previous best result (c + 1)H(min(Delta, k)) + O(1) in the case of m >= 1 + 1/(c - 1), where c is the best approximation ratio for Steiner tree, Delta is the maximum degree of the graph, k is the cardinality of the set of required vertices, m, is an optional integer satisfying 0 <= m <= min(Delta, k) and H is the harmonic function. This paper also proposes another approximation algorithm which is based on a greedy approach. The second algorithm can establish a worst case approximation ratio of 21n(min(Delta, k)) + O(1), which can also be improved to 21nk if the optimal solution is greater than c(.)e(2c+1)/2(c+1).

关键词： approximation algorithm Steiner connected dominated set graph algorithm NP-hard

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PRIME:: A mass spectrum data mining tool for de novo sequencing and PTMs identification

PRIME:: A mass spectrum data mining tool for <i>de novo</i> ...

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2nd Tsinghua International Bioinformatics Workshop

作者： Yan, B Qu, YX Mao, FL Olman, VN Xu, Y Univ Georgia Dept Biochem & Mol Biol Computat Syst Biol Lab Athens GA 30602 USA Oak Ridge Natl Lab Computat Biol Inst Oak Ridge TN 37831 USA

De novo sequencing is one of the most promising proteomics techniques for identification of protein post-translation modifications (PTMs) in studying protein regulations and functions. We have developed a computer tool PRIME for identification of b and y ions in tandem mass spectra, a key challenging problem in de novo sequencing. PRIME utilizes a feature that ions of the same and different types follow different mass-difference distributions to separate b from y ions correctly. We have formulated the problem as a graph partition problem. A linear integer-programming algorithm has been implemented to solve the graph partition problem rigorously and efficiently. The performance of PRIME has been demonstrated on a large amount of simulated tandem mass spectra derived from Yeast genome and its power of detecting PTMs has been tested on 216 simulated phosphopeptides.

关键词： de novo sequencing graph algorithm protein post-translational modifications proteomics tandem mass spectrometry

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PSgraph: How Tencent trains extremely large-scale graphs with Spark? 36

PSGraph: How Tencent trains extremely large-scale graphs wit...

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IEEE 36th International Conference on Data Engineering (ICDE)

作者： Jiang, Jiawei Xiao, Pin Yu, Lele Li, Xiaosen Cheng, Jiefeng Miao, Xupeng Zhang, Zhipeng Cui, Bin Swiss Fed Inst Technol Dept Comp Sci Zurich Switzerland Tencent Inc TEG Data Platform Shenzhen Peoples R China Peking Univ Sch EECS & MOE Beijing Peoples R China

ISBN: (纸本)9781728129037

Spark has extensively used in many applications of Tencent, due to its easy deployment, pipeline capability, and close integration with the Hadoop ecosystem. As the graph computing engine of Spark, graphX is also widely deployed to process large-scale graph data in Tencent. However, when the size of the graph data is up to billion-scale, graphX encounters serious performance degradation. Worse, graphx cannot support the rising advancement of graph embedding (GE) and graph neural network (GNN) algorithms. To address these challenges, we develop a new graph processing system, called PSgraph, which uses Spark executor and PyTorch to perform calculation, and develops a distributed parameter server to store frequently accessed models. PSgraph can train extremely large-scale graph data in Tencent with the parameter server architecture, and enable the training of GE and GNN algorithms. Moreover, PSgraph still benefits from the advantages of Spark via staying inside the Spark ecosystem, and can directly replace graphX without modification to the existing application framework. Our experiments show that PSgraph outperforms graphX significantly.

关键词： graph algorithm Spark parameter server

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New Approximation algorithms for the Rooted Budgeted Cycle Cover Problem 1

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15th Annual International Conference on Combinatorial Optimization and Applications (COCOA)

作者： Li, Jiangkun Zhang, Peng Shandong Univ Sch Software Jinan 250101 Shandong Peoples R China

ISBN: (数字)9783030926816

ISBN: (纸本)9783030926816;9783030926809

The rooted Budgeted Cycle Cover (BCC) problem is a fundamental optimization problem arising in wireless sensor networks and vehicle routing. Given a metric space (V, w) with vertex set V consisting of two parts D (containing depots) and V \ D (containing nodes), and a budget B >= 0, the rooted BCC problem asks to find a minimum number of cycles such that each cycle has length at most B and must contain a depot in D, and that these cycles collectively cover all the nodes in V \ D. In this paper, we give new approximation algorithms for the rooted BCC problem. For the rooted BCC problem with single depot, we give an O(log B/mu)-approximation algorithm, where mu is the minimum distance. For the rooted BCC problem with multiple depots, we give an O(log n)-approximation algorithm, where n is the number of vertices. Experiments show that our algorithms have good performance in practice.

关键词： Budgeted cycle cover Wireless sensor network graph algorithm Approximation algorithm Combinatorial optimization

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Dynamic Maxflow via Dynamic Interior Point Methods 2023

Dynamic Maxflow via Dynamic Interior Point Methods

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55th Annual ACM Symposium on Theory of Computing (STOC) part of the ACM Federated Computing Research Conference (FCRC)

作者： van den Brand, Jan Liu, Yang P. Sidford, Aaron Georgia Inst Technol Atlanta GA 30332 USA Stanford Univ Stanford CA USA

ISBN: (纸本)9781450399135

In this paper we provide an algorithm for maintaining a (1 - epsilon)-approximate maximum flow in a dynamic, capacitated graph undergoing edge insertions. Over a sequence of m insertions to an n-node graph where every edge has capacity O(poly(m)) our algorithm runs in time (O) over cap (m root n . epsilon(-1)).(1) To obtain this result we design dynamic data structures for the more general problem of detecting when the value of the minimum cost circulation in a dynamic graph undergoing edge insertions achieves value at most F (exactly) for a given threshold F. Over a sequence m insertions to an n-node graph where every edge has capacity O(poly(m)) and cost O(poly(m)) we solve this thresholded minimum cost flow problem in (O) over cap (m root n). Both of our algorithms succeed with high probability against an adaptive adversary. We obtain these results by dynamizing the recent interior point method by [Chen et al. FOCS 2022] used to obtain an almost linear time algorithm for minimum cost flow, and introducing a new dynamic data structure for maintaining minimum ratio cycles in an undirected graph that succeeds with high probability against adaptive adversaries.

关键词： dynamic algorithm graph algorithm maximum flow minimum cost flow bipartite matching

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Recognition Of Incomplete Objects Based On Synthesis Of Views Using A Geometric Based Local-Global graphs

Recognition Of Incomplete Objects Based On Synthesis Of View...

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作者： Michael Christopher Robbeloth Wright State University

学位级别：博士

The recognition of single objects is an old research field with many techniques and robust results. The probabilistic recognition of incomplete objects, however, remains an active field with challenging issues associated to shadows, illumination and other visual characteristics. With object incompleteness, we mean missing parts of a known object and not low-resolution images of that object. The employment of various single machine-learning methodologies for accurate classification of the incomplete objects did not provide a robust answer to the challenging problem. In this dissertation, we present a suite of high-level, model-based computer vision techniques encompassing both geometric and machine learning approaches to generate probabilistic matches of objects with varying degrees and forms of non-deformed incompleteness. The recognition of incomplete objects requires the formulation of a database of six sided views (e.g., model) of an object from which an identification can be made. The images are preprocessed (K-means segmentation, and region growing code to generate fully defined region and segment image information) from which local and global geometric and characteristic properties are generated in a process known as the Local-Global (L-G) graph method. The characteristic properties are then stored into a database for processing against sample images featuring various types of missing features. The sample images are then characterized in the same manner. After this, a suite of methodologies is employed to match a sample against an exemplar image in a multithreaded manner. The approaches, which work with the multi-view model database characteristics in a parallel (e.g, multithreaded manner) determine probabilistically by application of weighted outcomes the application of various matching routines. These routines include treating segment border regions as chain codes which are then processed using various string matching algorithms, the matching by center of mo

关键词： Computer Science incomplete objects obstruction Local-Global L-G graph synthesis of views recognition six-sided views multi-view chain code geometric segmentation computer vision image processing graph algorithm machine learning Delaunay triangulations

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THE SERIAL TRANSITIVE CLOSURE PROBLEM FOR TREES

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SIAM JOURNAL ON COMPUTING 1995年第1期24卷 109-122页

作者： BONET, ML BUSS, SR UNIV CALIF SAN DIEGO DEPT MATH LA JOLLA CA 92093 USA

The serial transitive closure problem is the problem, given a directed graph G and a list of edges, called closure edges, which are in the transitive closure of the graph, to generate all the closure edges from edges in G. A nearly linear upper bound is given on the number of steps in optimal solutions to the serial transitive closure problem for the case of graphs that are trees. ''Nearly linear'' means O(***(n)), where alpha is the inverse Ackermann function. This upper bound is optimal to within a constant factor.

关键词： TRANSITIVE CLOSURE graph algorithm INVERSE ACKERMANN FUNCTION WEAK SUPERCONCENTRATORS

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Hardness Results of Connected Power Domination for Bipartite graphs and Chordal graphs 15th

Hardness Results of Connected Power Domination for Bipartite...

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15th Annual International Conference on Combinatorial Optimization and Applications (COCOA)

作者： Goyal, Pooja Panda, B. S. Indian Inst Technol Delhi Dept Math Comp Sci & Applicat Grp Hauz Khas New Delhi 110016 India

ISBN: (纸本)9783030926816;9783030926809

A set D subset of V of a graph G = (V, E) is called a connected power dominating set of G if G[D], the subgraph induced by D, is connected and every vertex in the graph can be observed from D, following the two observation rules for power system monitoring: Rule 1: if v is an element of D, then v can observe itself and all its neighbors, and Rule 2: for an already observed vertex whose all neighbors except one are observed, then the only unobserved neighbor becomes observed as well. MINIMUM CONNECTED POWER DOMINATION PROBLEM is to find a connected power dominating set of minimum cardinality of a given graph G and Decide CONNECTED POWER DOMINATION PROBLEM is the decision version of MINIMUM CONNECTED POWER DOMINATION PROBLEM. DECIDE CONNECTED POWER DOMINATION PROBLEM is known to be NP-complete for general graphs. In this paper, we strengthen this result by proving that DECIDE CONNECTED POWER DOMINATION PROBLEM remains NP-complete for perfect elimination bipartite graph, a proper subclass of bipartite graphs, and split graphs, a proper subclass of chordal graphs. On the positive side, we show that MINIMUM CONNECTED POWER DOMINATION PROBLEM is polynomial-time solvable for chain graphs, a proper subclass of perfect elimination bipartite graph, and for threshold graphs, a proper subclass of split graphs. Further, we show that MINIMUM CONNECTED POWER DOMINATION PROBLEM cannot be approximated within (1 - epsilon) ln vertical bar V vertical bar for any epsilon > 0 unless P = NP, for bipartite graphs as well as for chordal graphs.

关键词： Connected power domination NP-complete graph algorithm

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StepTC: Stepwise Triangle Counting on GPU with Two Efficient Set Intersection Methods 29th

StepTC: Stepwise Triangle Counting on GPU with Two Efficient...

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29th International Conference on Database Systems for Advanced Applications (DASFAA)

作者： Tang, Jiahao Li, Zhixiong Huang, Jianqiang Qinghai Univ Intelligent Comp & Applicat Lab Qinghai Prov Qinghai Univ Xining 810016 Qinghai Peoples R China

ISBN: (纸本)9789819755615;9789819755622

Triangle counting (TC) plays a vital role in graph mining systems. However, existing methods often rely on single intersection kernel function, limiting their performance across diverse datasets. To address this challenge, we proposed StepTC (a novel Stepwise Triangle Counting algorithm). StepTC selects appropriate set intersection methods for each counting step to ensure optimal efficiency on a global scale. Additionally, two efficient set intersection methods and a dynamic shared memory assignment strategy are implemented to enhance the adaptability of StepTC for GPUs. A round-robin scheduling strategy for task partitioning is employed to achieve load balancing across multiple GPUs. It is noteworthy that StepTC outperforms state-of-the-art solutions, delivering impressive speedups ranging from 1.4x to 22.4x on various datasets.

关键词： Triangle counting Set intersection graph algorithm GPU

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Optimal algorithms for graphs and Images on a Shared Memory Mesh 30

Optimal Algorithms for Graphs and Images on a Shared Memory ...

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30th IEEE International Parallel and Distributed Processing Symposium (IPDPS)

作者： An, Yujie Stout, Quentin F. Univ Michigan Comp Sci & Engn Ann Arbor MI 48109 USA

ISBN: (纸本)9781509021406

In this paper we combine aspects of the PRAM and mesh models to achieve the benefits of each. Many fast algorithms are known for the PRAM, but it is unrealistic to build. Another well-known model is the 2-dimensional mesh, of which many have been built, but the algorithms are constrained by the mesh's diameter and bisection bandwidth, forcing algorithms for nontrivial problems to take time which is at least the square root of the number of processors. Here we use a minuscule amount of shared memory to make a practical design which is significantly faster than the standard mesh. We call this the shared memory mesh. We give several algorithms which show that a small amount of shared memory can significantly reduce the time for problems such as finding the median, labeling the connected components of an image, and labeling the connected components of a graph. Further, we show that many of these algorithms are optimal.

关键词： parallel computing mesh shared memory graph algorithm image processing connected component minimum spanning tree

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