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hugo-cwpearson/content/project/graph_library/index.md
2020-04-20 16:27:24 -05:00

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---
title: Graph Library
summary: Accelerating Static Graph Operations
tags:
- impact
- c3sr
date: "2016-04-27T00:00:00Z"
# Optional external URL for project (replaces project detail page).
external_link: ""
image:
caption:
focal_point: Smart
links:
- icon: github
icon_pack: fab
name: Pangolin Graph Library
url: https://github.com/c3sr/pangolin
- icon: link
icon_pack: fa
name: Pangolin C++ API Documentation
url: https://pangolin-docs.netlify.app/
- icon: github
icon_pack: fab
name: Graph Challenge
url: https://github.com/c3sr/graph_challenge
- icon: github
icon_pack: fab
name: Graph Dataset Tools
url: https://github.com/cwpearson/graph-datasets2
- icon: link
icon_pack: fa
name: Graph Dataset Statistics
url: https://graph-datasets-stats.netlify.com
url_code: ""
url_pdf: ""
url_slides: ""
url_video: ""
# Slides (optional).
# Associate this project with Markdown slides.
# Simply enter your slide deck's filename without extension.
# E.g. `slides = "example-slides"` references `content/slides/example-slides.md`.
# Otherwise, set `slides = ""`.
slides: ""
---
This project grew out of a 2018 graph challenge submission that I was tangentially involved in.
In 2019 I took charge of the triangle counting submission, where I implemented a variety of GPU triangle counting approaches.
This library contains those implementations, as well as k-truss decompositions written by my colleague Mohammad Almasri.
It also contains a fair amount of utility code, including sparse and dense data structures, system topology discovery code and search/load-balancing algorithms.