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A Case Study of Complex Graph Analysis in Distributed Memory: Implementation and Optimization
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/3-540-45591-4_68openalex-snapshot
On Identifying Strongly Connected Components in Parallel
inferredcites →https://doi.org/10.1007/978-3-319-07959-2_30openalex-snapshot
Partitioning Complex Networks via Size-Constrained Clustering
inferredcites →https://doi.org/10.1080/15427951.2009.10129177openalex-snapshot
Community Structure in Large Networks: Natural Cluster Sizes and the Absence of Large Well-Defined Clusters
inferredcites →https://doi.org/10.1103/physreve.76.036106openalex-snapshot
Near linear time algorithm to detect community structures in large-scale networks
inferredcites →https://doi.org/10.1109/bigdata.2014.7004265openalex-snapshot
PuLP: Scalable multi-objective multi-constraint partitioning for small-world networks
inferredcites →https://doi.org/10.1109/hpec.2012.6408680openalex-snapshot
STINGER: High performance data structure for streaming graphs
inferredcites →https://doi.org/10.1109/icdm.2009.14openalex-snapshot
PEGASUS: A Peta-Scale Graph Mining System Implementation and Observations
inferredcites →https://doi.org/10.1109/ipdps.2013.72openalex-snapshot
Scaling Techniques for Massive Scale-Free Graphs in Distributed (External) Memory
inferredcites →https://doi.org/10.1109/ipdps.2014.52openalex-snapshot
Traversing Trillions of Edges in Real Time: Graph Exploration on Large-Scale Parallel Machines
inferredcites →https://doi.org/10.1109/ipdps.2014.64openalex-snapshot
BFS and Coloring-Based Parallel Algorithms for Strongly Connected Components and Related Problems
inferredcites →https://doi.org/10.1109/ipdps.2015.54openalex-snapshot
High-Performance Graph Analytics on Manycore Processors
inferredcites →https://doi.org/10.1109/ipdpsw.2014.155openalex-snapshot
Parallel Heuristics for Scalable Community Detection
inferredcites →https://doi.org/10.1137/1.9781611972740.43openalex-snapshot
R-MAT: A Recursive Model for Graph Mining
inferredcites →https://doi.org/10.1145/1993316.1993501openalex-snapshot
The tao of parallelism in algorithms
inferredcites →https://doi.org/10.1145/2567948.2576928openalex-snapshot
Graph structure in the web --- revisited
inferredcites →https://doi.org/10.1145/2588555.2610518openalex-snapshot
Navigating the maze of graph analytics frameworks using massive graph datasets
inferredcites →https://doi.org/10.1145/369028.369103openalex-snapshot
Parallel multilevel k-way partitioning scheme for irregular graphs
inferredcites →https://doi.org/10.1561/106.00000003openalex-snapshot
The Graph Structure in the Web − Analyzed on Different Aggregation Levels
inferredcites →https://doi.org/10.1609/icwsm.v4i1.14033openalex-snapshot
Measuring User Influence in Twitter: The Million Follower Fallacy
inferredcites →https://doi.org/10.48550/arxiv.1408.0500openalex-snapshot
FlashGraph: Processing Billion-Node Graphs on an Array of Commodity SSDs
inferredcites →https://doi.org/10.48550/arxiv.1412.8576openalex-snapshot
Active Community Detection in Massive Graphs
inferredcites →https://doi.org/10.5555/2387880.2387883openalex-snapshot
PowerGraph: distributed graph-parallel computation on natural graphs
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-981-95-1365-9_1openalex-snapshot
Search, Rescue, Repeat: Maze Path Finding Algorithms
inferred← citeshttps://doi.org/10.1007/s42514-021-00070-zopenalex-snapshot
VPC: Pruning connected components using vector-based path compression for Graph500
inferred← citeshttps://doi.org/10.1016/j.jpdc.2020.04.009openalex-snapshot
Parallel algorithms for finding connected components using linear algebra
inferred← citeshttps://doi.org/10.1016/j.parco.2022.102896openalex-snapshot
Parallel graph coloring algorithms for distributed GPU environments
inferred← citeshttps://doi.org/10.1109/access.2019.2949836openalex-snapshot
Toward High-Performance Computing and Big Data Analytics Convergence: The Case of Spark-DIY
inferred← citeshttps://doi.org/10.1109/bigdata50022.2020.9378152openalex-snapshot
Centrality and Scalability Analysis on Distributed Graph of Large-Scale E-mail Dataset for Digital Forensics
inferred← citeshttps://doi.org/10.1109/bigdata62323.2024.10825675openalex-snapshot
Fast Distributed Memory Parallel Algorithms for Finding Connected Components in Large Graphs
inferred← citeshttps://doi.org/10.1109/dcabes.2017.34openalex-snapshot
Application of Distributed Storage Technology for Financial Management and Control System in Electric Power System
inferred← citeshttps://doi.org/10.1109/hipc58850.2023.00022openalex-snapshot
Contour Algorithm for Connectivity
inferred← citeshttps://doi.org/10.1109/hpec62836.2024.10938460openalex-snapshot
Constant-Memory Graph Coarsening
inferred← citeshttps://doi.org/10.1109/ia351965.2020.00013openalex-snapshot
Distributed Memory Graph Coloring Algorithms for Multiple GPUs
inferred← citeshttps://doi.org/10.1109/ipdps.2017.95openalex-snapshot
Partitioning Trillion-Edge Graphs in Minutes
inferred← citeshttps://doi.org/10.1109/ipdps.2019.00012openalex-snapshot
LACC: A Linear-Algebraic Algorithm for Finding Connected Components in Distributed Memory
inferred← citeshttps://doi.org/10.1109/ipdpsw.2017.164openalex-snapshot
Order or Shuffle: Empirically Evaluating Vertex Order Impact on Parallel Graph Computations
inferred← citeshttps://doi.org/10.1109/sc.2018.00061openalex-snapshot
iSpan: Parallel Identification of Strongly Connected Components with Spanning Trees
inferred← citeshttps://doi.org/10.1109/sc41406.2024.00050openalex-snapshot
KaMPIng: Flexible and (Near) Zero-Overhead C++ Bindings for MPI
inferred← citeshttps://doi.org/10.1109/tpds.2017.2672739openalex-snapshot
An Adaptive Parallel Algorithm for Computing Connected Components
inferred← citeshttps://doi.org/10.1109/tpds.2017.2743708openalex-snapshot
GraphD: Distributed Vertex-Centric Graph Processing Beyond the Memory Limit
inferred← citeshttps://doi.org/10.1109/tpds.2020.3002150openalex-snapshot
Scalable, Multi-Constraint, Complex-Objective Graph Partitioning
inferred← citeshttps://doi.org/10.1109/tsc.2025.3562342openalex-snapshot
Towards Hybrid Architectures for Big Data Analytics: Insights From Spark-MPI Integration
inferred← citeshttps://doi.org/10.1145/3210377.3210414openalex-snapshot
Theoretically Efficient Parallel Graph Algorithms Can Be Fast and Scalable
inferred← citeshttps://doi.org/10.1145/3219819.3219927openalex-snapshot
Accelerating Large-Scale Data Analysis by Offloading to High-Performance Computing Libraries using Alchemist
inferred← citeshttps://doi.org/10.1145/3295500.3356206openalex-snapshot
Scalable generation of graphs for benchmarking HPC community-detection algorithms
inferred← citeshttps://doi.org/10.1145/3754598.3754664openalex-snapshot
Scaling Distributed Graph Processing to Hundreds of GPUs
inferred← citeshttps://doi.org/10.1155/2021/9943289openalex-snapshot
Accelerating Spark‐Based Applications with MPI and OpenACC
inferred← citeshttps://doi.org/10.14778/3090163.3090168openalex-snapshot
Bridging the gap between HPC and big data frameworks
inferred← citeshttps://doi.org/10.48550/arxiv.1701.00503openalex-snapshot
Distributed Graph Layout for Scalable Small-world Network Analysis
inferred← citeshttps://doi.org/10.48550/arxiv.2008.03909openalex-snapshot
ConnectIt: A Framework for Static and Incremental Parallel Graph Connectivity Algorithms
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