Ligra: A Lightweight Graph Processing Framework for Shared Memory J. - - PowerPoint PPT Presentation

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Ligra: A Lightweight Graph Processing Framework for Shared Memory J. - - PowerPoint PPT Presentation

May 23, 2023 752 likes •979 views

Ligra: A Lightweight Graph Processing Framework for Shared Memory J. Shun and G. Blelloch Presented by Dmitry Kazhdan Overview Background (briefly) Existing work Key contributions Results Criticism Conclusions

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SLIDE 1
  • J. Shun and G. Blelloch

Ligra: A Lightweight Graph Processing Framework for Shared Memory

Presented by Dmitry Kazhdan

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SLIDE 2

Overview

  • Background (briefly)
  • Existing work
  • Key contributions
  • Results
  • Criticism
  • Conclusions
  • Questions
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SLIDE 3

Background

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SLIDE 4

Background

Motivation:

  • Efficient Graph Processing

Opportunities:

  • Parallelism
  • Large number of cores + RAM in a single server
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SLIDE 5

Related Work

  • Pregel
  • PowerGraph
  • Green-Marl
  • X-Stream
  • Pegasus
  • GraphLab
  • …
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SLIDE 6

Ligra

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SLIDE 7

Ligra

  • Graph processing framework
  • Relying on multicore machines with shared memory
  • Offering parallel processing
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Contributions

  • Implemented in memory (single machine)
  • Lightweight (contains a few thousand lines of C++)
  • Easily extendable/customisable
  • Minimal (offering a small number of primitives/abstractions)
  • Ligra+ offers graph compression
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SLIDE 9

Abstractions

  • Graph and VertexSubset datatypes.
  • EdgeMap and VertexMap functions.
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SLIDE 10

Use Cases

  • Breadth-first Search
  • Betweenness Centrality
  • Graph Radii Estimation
  • Connected Components
  • Page Rank
  • Bellman-Ford Shortest Paths
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SLIDE 11

Evaluation

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SLIDE 12

Evaluation

  • Evaluated algorithm performance on set
  • f selected graphs
  • Showed effects of using more threads
  • Gave performance comparisons to other

systems (albeit brief, often using different setups)

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SLIDE 13

Evaluation

  • Showed system scalability on randomly generated graphs
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SLIDE 14

Resources

http://jshun.github.io/ligra/index.html https://github.com/jshun/ligra

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Criticism

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Criticism/Discussion

“and our code is much simpler than theirs”

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Criticism/Discussion

  • How representative are the examples?
  • Too much time spent describing algorithms
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Criticism/Discussion

  • Single experimental setup (“but the results are slower than the ones from the

Intel machine so we only report the latter”)

  • Performance comparisons not detailed or not meaningful (“we achieved faster

results”)

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SLIDE 19

Conclusions

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SLIDE 20

Conclusions

  • Introduced Ligra
  • Compared to existing systems
  • Presented evaluation results
  • Criticism
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SLIDE 21

Questions?