2015 IEEE International Conference on Big Data (Big Data) 2015
DOI: 10.1109/bigdata.2015.7363954
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DISTINGER: A distributed graph data structure for massive dynamic graph processing

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Cited by 25 publications
(12 citation statements)
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References 18 publications
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“…Makkar et al [171] presented an exact and parallel approach using an inclusion-exclusion formulation for triangle counting in dynamic graphs. The algorithm is implemented in cuSTINGER [86] and runs on GPUs. The algorithm computes updates for batches of edge updates and also updates the number of triangles each vertex belongs to.…”
Section: Motif Search and Motif Countingmentioning
confidence: 99%
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“…Makkar et al [171] presented an exact and parallel approach using an inclusion-exclusion formulation for triangle counting in dynamic graphs. The algorithm is implemented in cuSTINGER [86] and runs on GPUs. The algorithm computes updates for batches of edge updates and also updates the number of triangles each vertex belongs to.…”
Section: Motif Search and Motif Countingmentioning
confidence: 99%
“…The authors already implemented a variety of algorithms on STINGER including community detection, -core extraction, and many more. Later, Feng et al [86] presented DISTINGER which has the same goals as STINGER, but focuses on the distributed memory case, i.e. the authors presented a distributed graph representation.…”
Section: Dynamic Graph Systemsmentioning
confidence: 99%
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“…These works propose data structures that try to achieve the sequential read capabilities of CSR while being more optimized for writes. Example systems and data structures include LiveGraph [62], Aspen [31], LLAMA [49], STINGER [32], and DISTINGER [34]. In this paper we focused on a read-optimized system setting and implemented our techniques inside GraphflowDB, which we are designing as a read-optimized system.…”
Section: Related Workmentioning
confidence: 99%
“…Graph streaming frameworks such as STINGER [76] or Aspen [63] emerged to enable processing and analyzing dynamically evolving graphs. Contrarily to static frameworks such as Ligra [190], [98], such systems execute graph analytics algorithms (e.g., PageRank) concurrently with graph updates (e.g., edge insertions).…”
Section: Introductionmentioning
confidence: 99%