networkit: an interactive tool suite for high-performance network

– NetworKit: An Interactive Tool Suite for High-Performance Network Analysis 1

A NetworKit Tutorial

www.kit.eduKIT – University of the State of Baden-Wuerttemberg andNational Laboratory of the Helmholtz Association

INSTITUTE OF THEORETICAL INFORMATICS · PARALLEL COMPUTING GROUP


Introduction | Complex Networks

Non-trivial topological features that do not occur in simple networks(meshes, simple random graphs), but often occur in reality

Small diameterStrongly varying degree distributionLarge number of triangles...


Introduction | Network Science

Often

exploratory in nature

requires data preprocessing toextract graph

creates large data sets easily

requires domain-specific post-processing for interpretation

”Statistics of relational data”

image: sayasaya2011.wordpress.com/

→ Fast interactive toolkit required!


Introduction | Toolkit Design Goals

Performance

Implementation with efficiency and parallelism in mind

Interface

Exploratory workflows→ freely combinable functions and interactive interface

Integration

Seamless integration with Python ecosystemfor scientific computing and data analysis

Target Platforms

Shared-memory parallel computers

Multicore PCs, workstations, compute servers . . .


Introduction | NetworKit: Architecture


Introduction | NetworKit: Overview

Languages: C++, Python

Parallelism: Shared memory (OpenMP)

License: MIT

First release: 1.0 (March 2013)

Web: https://networkit.iti.kit.edu


Introduction | NetworKit: Graph Data Structure

graph implementation

graph API

image: algs4.cs.princeton.edu


NetworKit for theProgramming Projects


Download Mercurial (https://www.mercurial-scm.org)

Create an account on https://algohub.iti.kit.edu/

Send an e-mail to [email protected]

specifying your username and group number

Groups:

1. Graph Clustering, Tobias Lorenz and Johannes Ernst2. Partitioning, Michael Schrempp and Katharina Flugel3. TSP, Henning Dieterichs and Michael Wiegner4. Mapping, Holger Klein and Jasmin Hoffmann5. Framework, Tabu search, Sarah Dold and Sidney Bender


Clone the NetworKit fork corresponding to your group, e.g.hg clone https://[email protected]/parco/

NetworKit/NetworKit-AMfsO-Group1

Remember to work on the Dev branch!

hg up Dev

Before starting:

Read some code to get used to the code style and try to adoptit whenever possibleRead the DevGuide on the website:https://networkit.iti.kit.edu/api/DevGuide.html


Installing NetworKit


Building the C++ Core

Requirements:

modern C++ compiler, e.g.: g++ (≥ 4.8) or clang++ (≥ 3.7)SConsGoogle Test

https://networkit.iti.kit.edu/get_started.html#

building-only-the-c-core

Building executable for unit tests:

Copy build.conf.example to build.conf and edit your envi-ronment settingsscons --optimize=Dbg --target=Tests

Running unit tests

./NetworKit-Tests-Dbg --gtest filter=*Closeness*


Developing new classes

C++ classes:

networkit/cpp/ + subdirectories (corresponding to mod-ules on the python level)GTest: networkit/cpp/ + subdir + test

Always test your classes!

Exposing to Python: networkit/ NetworKit.pyx

https://networkit.iti.kit.edu/api/DevGuide.html#

exposing-c-code-to-python

Add your class to *.py file in the networkit folder

Always refer to the DevGuide on the website!!


Using NetworKit with IPython

Installation:

pip3 install -e ./

If you don’t have ipython and jupyter yet...

pip3 install ipython

pip3 install jupyter

Open jupyter notebook


Exercise


Read the file input/wiki-Vote.txt (format =EdgeListTabZero)

Compute:

1. Number of nodes and edges2. Number of connected components and size of the largest

connected component3. Node with maximum degree

networkit: an interactive tool suite for high-performance network

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