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3rd Russian Supercomputing Days (RuSCDays)

作者： Afanasyev, Ilya Voevodin, Vladimir Lomonosov Moscow State Univ Moscow Russia

ISBN: (纸本)9783319712543;9783319712550

The paper describes implementation approaches to large-graph processing on two modern high-performance computational platforms: NVIDIA GPU and Intel KNL. The described approach is based on a deep a priori analysis of algorithm properties that helps to choose implementation method correctly. To demonstrate the proposed approach, shortest paths and strongly connected components computation problems have been solved for sparse graphs. The results include detailed description of the whole algorithm's development cycle: from algorithm information structure research and selection of efficient implementation methods, suitable for the particular platforms, to specific optimizations for each of the architectures. Based on the joint analysis of algorithm properties and architecture features, a performance tuning, including graph storage format optimizations, efficient usage of the memory hierarchy and vectorization is performed. The developed implementations demonstrate high performance and good scalability of the proposed solutions. In addition, a lot of attention was paid to profiling implemented algorithms with NVIDIA Visual Profiler and Intel (R) VTune (TM) Amplifier utilities. This allows current paper to present a fair comparison, demonstrating advantages and disadvantages of each platform for large-scale graph processing.

关键词： graph algorithms GPU KNL CUDA Vectorization SSSP SCC Large-scale graph processing

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Applications of graph Segmentation algorithms For Quantitative Genomic Analyses

Applications of Graph Segmentation Algorithms For Quantitati...

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作者： Gunady, Mohamed University of Maryland

学位级别：博士

There is a growing interest in utilizing graph formulations and graph-based algorithms in different subproblems of genomic analysis. Since graphs provide a natural and efficient representation of sequences of data where some structural relationships are observed within the data, we study some graph applications in quantitative analysis of typical RNA-seq and Whole Genome Sequencing pipelines. Analysis of differential alternative splicing from RNA-seq data is complicated by the fact that many RNA-seq reads map to multiple transcripts, besides, the annotated transcripts are often a small subset of the possible transcripts of a gene. This work describes Yanagi, a tool for segmenting transcriptomes to create a library of maximal L-disjoint segments from a complete transcriptome annotation. That segment library preserves transcriptome substrings and structural relationships between transcripts while eliminating unnecessary sequence duplications. First, we formalize the concept of transcriptome segmentation and propose an efficient algorithm for generating segment libraries. The resulting segment sequences can be used with pseudo-alignment tools to quantify gene expression and alternative splicing at the segment level and provide gene-level visualization of the segments for more interpretability. The notion of transcript segmentation as introduced here and implemented in Yanagi opens the door for the application of lightweight, ultra-fast pseudo-alignment algorithms in a wide variety of RNA-seq analyses. Furthermore, we show how transcriptome quantification can be performed from segment-level statistics. We present an EM algorithm that uses segment counts as features to estimate transcripts relative abundances in a way that maximizes the likelihood of the observed sequenced data. Then we tackle the problem of quantification in an incomplete annotation setting. We propose an assembly-free correction procedure that reduces bias in the estimated abundances of the annotate

关键词： Bioinformatics Computer science Alternative Splicing graph algorithms Population Reference graph RNA-seq scRNA-seq Transcriptome Quantification

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Locality Analysis of graph Reordering algorithms 17

Locality Analysis of Graph Reordering Algorithms

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17th IEEE International Symposium on Workload Characterization (IISWC)

作者： Esfahani, Mohsen Koohi Kilpatrick, Peter Vandierendonck, Hans Queens Univ Belfast Belfast Antrim North Ireland

ISBN: (纸本)9781665441735

A major challenge in processing real-world graphs stems from poor locality of memory accesses and vertex reordering algorithms (RAs) have been proposed to improve locality by changing the order of memory accesses. While state-of-the-art RAs like SlashBurn, GOrder, and Rabbit-Order effectively speed up graph algorithms, their capabilities and disadvantages are not fully understood, mainly, for three reasons: (1) the large size of datasets, (2) the lack of suitable measurement tools, and (3) disparate characteristics of graphs. The paucity of analysis has also inhibited the design of more efficient RAs. This paper unlocks this black box by introducing a number of tools, including: (1) a cache simulation technique for processing large graphs, (2) the Neighbour to Neighbour Average ID Distance (N2N AID) as a spatial locality metric, (3) the degree distributions of simulated cache miss rate and AID to investigate how locality of different vertices is affected by RAs, and (4) "effective cache size" to measure how much of cache capacity is used to support random accesses. We introduce (1) asymmetricity degree distribution, (2) degree range decomposition, and (3) push and pull locality to present a structural analysis of different types of real-world graphs by explaining their contrasting behaviours in confronting RAs. Finally, we propose a number of improvements for RAs using the analysis provided in this paper.

关键词： graph processing graph reordering Memory locality High performance computing graph algorithms

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Movie Recommendation Based on graph Traversal algorithms

Movie Recommendation Based on Graph Traversal Algorithms

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24th International Workshop on Database and Expert Systems Applications (DEXA)

作者： Demovic, Lubos Fritscher, Eduard Kriz, Jakub Kuzmik, Ondrej Proksa, Ondrej Vandlikova, Diana Zelenik, Dusan Bielikova, Maria Slovak Univ Technol Bratislava Fac Informat & Informat Technol Inst Informat & Software Engn Bratislava 84216 Slovakia

ISBN: (纸本)9780769550701

Media content recommendation is nowadays a common problem. Traditional algorithms based on collaborative filtering require an up-to-date dataset of users and their preferences, which is difficult to gather for huge database of items. Content-based approach suffers from the complex computation of similarity among items. In this paper we propose an approach to recommendation with a focus on the natural change of user's interests in movies. We make use of a graph representation and experimented with modified graph algorithms. We design a representation of the data about movies in a graph structure and a method which uses our data model for recommendation. We propose four recommendation algorithms which are capable to find recommendations based on initial nodes, which selection is based on the user's current interests. We implemented these algorithms and experimentally evaluated them with real users.

关键词： recommendation graph representation graph algorithms

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Cyberfilm specifications for generalized graph search algorithms

Cyberfilm specifications for generalized graph search algori...

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IASTED International Conference on Advances in Computer Science and Technology

作者： Watanobe, Yutaka Mirenkov, Nikolay N. Yoshioka, Rentaro Univ Aizu Grad Dept Informat Syst Aizu Wakamatsu Fukushima 9658580 Japan

ISBN: (纸本)0889865450

A multimedia programming approach for the generalized graph search (traversal) algorithms is considered. It is based on a concept of cyberFilm, which is a set of multi-media frames defining algorithmic features. Through these frames, the user can represent computational steps and specify "activity" within the steps. Each set of multimedia frames, represented by a special icon, is supported by a set of template programs to generate corresponding executable codes. Such icons and sets of template programs behind them provide powerful repetitive-type constructs for specifying computational algorithms. The main contributions of this paper are an introduction of a cyberFilm developed for the generalized graph search algorithms and a description of the template programs supporting this cyberFilm. 505-086 in display pdf

关键词： multimedia programming language graph algorithms CyberFilm template programs

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graph-based algorithms for Text Summarization

Graph-based algorithms for Text Summarization

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International Conference on Emerging Trends in Engineering and Technology

作者： Thakkar, Khushboo S. Dharaskar, R.V. Chandak, M.B. Department of Computer Science and Engineering G. H. Raisoni College of Engineering Nagpur India Dept. of Computer Science and Engineering Shri Ramdeobaba Kamla Nehru Engineering College Nagpur India

ISBN: (纸本)9780769542461

Summarization is a brief and accurate representation of input text such that the output covers the most important concepts of the source in a condensed manner. Text Summarization is an emerging technique for understanding the main purpose of any kind of documents. To visualize a large text document within a short duration and small visible area like PDA screen, summarization provides a greater flexibility and convenience. This paper presents innovative unsupervised methods for automatic sentence extraction using graph-based ranking algorithms and shortest path algorithm. © 2010 IEEE.

关键词： graph algorithms

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Risk Assessment of Unexpected Events in Universities: graph Theory algorithms in Complex System Networks

Risk Assessment of Unexpected Events in Universities: Graph ...

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2024 International Conference on Interactive Intelligent Systems and Techniques, IIST 2024

作者： Wang, Na Xi'an International Studies University Communist Youth League of China XISU Committee Xi'an China

ISBN: (纸本)9798350374421

With the continuous development of society, the risk assessment of unexpected events in universities has become increasingly important. This study aims to explore the application of graph theory algorithms in complex system networks, in order to improve the accuracy and reliability of emergency risk assessment in universities. This article considers various related factors, including various interaction relationships within and outside the school, introduces graph theory algorithms, and identifies potential risk factors and vulnerabilities by analyzing the network structure and the relationships between nodes. This article found through empirical case studies that the average prediction accuracy of graph theory algorithms in the application of complex system networks can reach 93.34%, demonstrating the effectiveness of graph theory algorithms and providing new ideas and methods for risk management of unexpected events in universities. © 2024 IEEE.

关键词： graph algorithms

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Summarization of Scientific Articles using Hybrid SciBERT and graph-Based algorithms 11

Summarization of Scientific Articles using Hybrid SciBERT an...

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11th International Conference on Electrical Engineering, Computer Science and Informatics, EECSI 2024

作者： Nugroho, Galang Setia Djamal, Esmeralda Contessa Ilyas, Ridwan Universitas Jenderal Achmad Yani Department of Informatics Cimahi Indonesia

ISBN: (纸本)9798350355314

In the ever-evolving information age, automatic text summarization is an important solution to address complex text processing problems, especially in scientific articles. Scientific articles often have complex structures and terminology, requiring methods to capture deep contextual meaning. This research proposes an extractive text summarization approach that combines SciBERT, a BERT-based language model developed specifically for scientific texts, with PageRank and HITS algorithms that are integrated using Harmonic Mean. SciBERT converts sentences in scientific articles into sentence vectors by combining the last four layers to produce optimal contextual embedding to preserve complex scientific meaning and context. Furthermore, PageRank and HITS algorithms rank sentences based on relevance and the relationship between sentences. Combining these two algorithms through the Harmonic Mean produces a more representative summary, balancing sentence relevance and overall text coherence. The approach was tested on the PubMed dataset, showing that the proposed model could produce summaries with ROUGE-1 scores reaching 32.23%, ROUGE-2 reaching 11.64%, and ROUGE-L reaching 29.18%. These results show that combining SciBERT with graph-based algorithms can effectively capture and retain important information in complex scientific texts while overcoming problems such as loss of context between sentences. © 2024 IEEE.

关键词： graph algorithms

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PASCO (PArallel Structured COarsening): an overlay to speed up graph clustering algorithms

arXiv

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arXiv 2024年

作者： Etienne, Lasalle Rémi, Vaudaine Titouan, Vayer Pierre, Borgnat Paulo, Gonçalves Rémi, Gribonval Márton, Karsai Inria ENS de Lyon CNRS Université Claude Bernard Lyon 1 LIP UMR 5668 Lyon69342 cedex 07 France CNRS ENS de Lyon LPENSL UMR5672 LyonF-69342 cedex 07 France Department of Network and Data Science Central European University Vienna1100 Austria National Laboratory for Health Security HUN-REN Alfréd Rényi Institute of Mathematics Budapest1053 Hungary

Clustering the nodes of a graph is a cornerstone of graph analysis and has been extensively studied. However, some popular methods are not suitable for very large graphs: e.g., spectral clustering requires the computation of the spectral decomposition of the Laplacian matrix, which is not applicable for large graphs with a large number of communities. This work introduces PASCO, an overlay that accelerates clustering algorithms. Our method consists of three steps: 1- We compute several independent small graphs representing the input graph by applying an efficient and structure-preserving coarsening algorithm. 2- A clustering algorithm is run in parallel onto each small graph and provides several partitions of the initial graph. 3- These partitions are aligned and combined with an optimal transport method to output the final partition. The PASCO framework is based on two key contributions: a novel global algorithm structure designed to enable parallelization and a fast, empirically validated graph coarsening algorithm that preserves structural properties. We demonstrate the strong performance of PASCO in terms of computational efficiency, structural preservation, and output partition quality, evaluated on both synthetic and real-world graph datasets. Copyright © 2024, The Authors. All rights reserved.

关键词： graph algorithms

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Efficient algorithms for Attributed graph Alignment with Vanishing Edge Correlation

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IEEE Transactions on Information Theory 2025年第6期71卷 4556-4580页

作者： Wang, Ziao Wang, Weina Wang, Lele University of British Columbia Department of Electrical and Computer Engineering VancouverBCV6T 1Z4 Canada University of Michigan Department of Electrical and Computer Engineering Ann ArborMI48109 United States Carnegie Mellon University Computer Science Department PittsburghPA15213 United States

graph alignment refers to the task of finding the vertex correspondence between two correlated graphs of n vertices. Extensive study has been done on polynomial-time algorithms for the graph alignment problem under the Erdős–Rényi graph pair model, where the two graphs are Erdős–Rényi graphs with edge probability qu, correlated under certain vertex correspondence. To achieve exact recovery of the correspondence, all existing algorithms at least require the edge correlation coefficient ρu between the two graphs to be non-vanishing as n → ∞. Moreover, it is conjectured that no polynomial-time algorithm can achieve exact recovery under vanishing edge correlation ρuu ≥ n-Θ(1). We identify a local tree structure, which incorporates one layer of user information and one layer of attribute information, and apply the subgraph counting technique to such structures. A polynomial-time algorithm is proposed that recovers the vertex correspondence for most of the vertices, and then refines the output to achieve exact recovery. The consideration of attribute information is motivated by real-world applications like LinkedIn and Twitter, where user attributes like birthplace and education background can aid alignment. © 1963-2012 IEEE.

关键词： graph algorithms

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