Suchergebnisse - "parallel graph algorithms"

GreediRIS: Scalable influence maximization using distributed streaming maximum cover von Barik, Reet, Cappa, Wade, Ferdous, S.M., Minutoli, Marco, Halappanavar, Mahantesh, Kalyanaraman, Ananth

“… Influence maximization—the problem of identifying a subset of k influential seeds (vertices) in a network—is a classical problem in network science with …”
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NetworKit: A tool suite for large-scale complex network analysis von STAUDT, CHRISTIAN L., SAZONOVS, ALEKSEJS, MEYERHENKE, HENNING

“… We introduce NetworKit, an open-source software package for analyzing the structure of large complex networks. Appropriate algorithmic solutions are required …”
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Towards scaling community detection on distributed-memory heterogeneous systems von Gawande, Nitin, Ghosh, Sayan, Halappanavar, Mahantesh, Tumeo, Antonino, Kalyanaraman, Ananth

“… In most real-world networks, nodes/vertices tend to be organized into tightly-knit modules known as communities or clusters such that nodes within a community …”
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Parallel Algorithm for Incremental Betweenness Centrality on Large Graphs von Jamour, Fuad, Skiadopoulos, Spiros, Kalnis, Panos

“… Betweenness centrality quantifies the importance of nodes in a graph in many applications, including network analysis, community detection and identification …”
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A memory efficient maximal clique enumeration method for sparse graphs with a parallel implementation von Yu, Ting, Liu, Mengchi

“… •We propose a memory efficient method, CMC-bit, for maximal clique enumeration on real-world sparse graphs.•We use an efficient order strategy to reduce both …”
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BFS-4K: An Efficient Implementation of BFS for Kepler GPU Architectures von Busato, Federico, Bombieri, Nicola

“… Breadth-first search (BFS) is one of the most common graph traversal algorithms and the building block for a wide range of graph applications. With the advent …”
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A performance predictor for implementation selection of parallelized static and temporal graph algorithms von Rehman, Akif, Ahmad, Masab, Khan, Omer

“… Task‐based execution of graph workloads allows various ordered and unordered implementations, with tasks representing dependencies between graph vertices and …”
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Performance Evaluation of Parallel Graphs Algorithms Utilizing Graphcore IPU von Gepner, Paweł, Kocot, Bartłomiej, Paprzycki, Marcin, Ganzha, Maria, Moroz, Leonid, Olas, Tomasz

“… Recent years have been characterized by increasing interest in graph computations. This trend can be related to the large number of potential application …”
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Graph coloring algorithms for multi-core and massively multithreaded architectures von Çatalyürek, Ümit V., Feo, John, Gebremedhin, Assefaw H., Halappanavar, Mahantesh, Pothen, Alex

“… ► We explore the interplay between architectures and algorithm design for graph problems. ► We target multi-core platforms and a massively multithreaded …”
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High-performance and balanced parallel graph coloring on multicore platforms von Giannoula, Christina, Peppas, Athanasios, Goumas, Georgios, Koziris, Nectarios

“… Graph coloring is widely used to parallelize scientific applications by identifying subsets of independent tasks that can be executed simultaneously. Graph …”
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Distributed Graph Diameter Approximation von Ceccarello, Matteo, Pietracaprina, Andrea, Pucci, Geppino, Upfal, Eli

“… We present an algorithm for approximating the diameter of massive weighted undirected graphs on distributed platforms supporting a MapReduce-like abstraction …”
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Optimizing Graph Algorithms in Asymmetric Multicore Processors von Krishna, Jyothi V.S., Nasre, Rupesh

“… Asymmetric multicore processors (AMP) fall under a special subcategory of modern-day heterogeneous multicore architectures with different participating core …”
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A scalable, parallel algorithm for maximal clique enumeration von Schmidt, Matthew C., Samatova, Nagiza F., Thomas, Kevin, Park, Byung-Hoon

“… The problem of maximal clique enumeration (MCE) is to enumerate all of the maximal cliques in a graph. Once enumerated, maximal cliques are widely used to …”
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Efficient GPU algorithms for parallel decomposition of graphs into strongly connected and maximal end components von Wijs, Anton, Katoen, Joost-Pieter, Bošnački, Dragan

“… This article presents parallel algorithms for component decomposition of graph structures on general purpose graphics processing units (GPUs). In particular, …”
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An Efficient GPU Implementation of Inclusion-Based Pointer Analysis von Su, Yu, Ye, Ding, Xue, Jingling, Liao, Xiang-Ke

“… We present an efficient GPU implementation of Andersen's whole-program inclusion-based pointer analysis, a fundamental analysis on which many others are based, …”
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A Brief Survey of Algorithms, Architectures, and Challenges toward Extreme-scale Graph Analytics von Kalyanaraman, Ananth, Pande, Partha Pratim

“… The notion of networks is inherent in the structure, function and behavior of the natural and engineered world that surround us. Consequently, graph models and …”
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A Shared-Memory Parallel Algorithm for Updating Single-Source Shortest Paths in Large Dynamic Networks von Srinivasan, Sriram, Riazi, Sara, Norris, Boyana, Das, Sajal K., Bhowmick, Sanjukta

“… Computing the single-source shortest path (SSSP) is one of the fundamental graph algorithms, and is used in many applications. Here, we focus on computing SSSP …”
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High-performance parallel frequent subgraph discovery von Shahrivari, Saeed, Jalili, Saeed

“… Discovery of frequent subgraphs of an input network is one of the most important facilities for mining and analyzing complex networks. The most accurate …”
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A new augmentation based algorithm for extracting maximal chordal subgraphs von Bhowmick, Sanjukta, Chen, Tzu-Yi, Halappanavar, Mahantesh

“… A graph is chordal if every cycle of length greater than three contains an edge between non-adjacent vertices. Chordal graphs are of interest both …”
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MR-search: massively parallel heuristic search von Schütt, Thorsten, Reinefeld, Alexander, Maier, Robert

“… SUMMARY MR‐Search is a framework for massively parallel heuristic search. Based on the MapReduce paradigm, it efficiently utilizes all available resources: …”
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