VieCut 1.00

VieCut is a library of shared-memory parallel algorithms for the minimum cut problem on undirected edge-weighted graphs. Part of the KaHIP organization.

Python Interface: An easy-to-use Python interface for this software is available in CHSZLabLib.

What it solves	Find the minimum edge cut that separates a graph into two (or more) components
Algorithms	Inexact heuristic (VieCut), exact parallel (NOI-based), cactus representation, multiterminal cut
Parallelism	Shared-memory via OpenMP; sequential versions included
Interfaces	CLI
Requires	C++17 compiler, CMake 3.9+, OpenMP, MPI (multiterminal cut only)

Quick Start

Install via Homebrew (Linux only)

brew install KaHIP/kahip/viecut

Or build from source

git clone --recursive https://github.com/KaHIP/VieCut.git && cd VieCut
mkdir build && cd build && cmake .. -DCMAKE_BUILD_TYPE=Release -DUSE_TCMALLOC=OFF && make

Run

# Heuristic minimum cut (fast, near-optimal)
./build/mincut network.graph vc

# Exact minimum cut (parallel)
./build/mincut_parallel network.graph exact

# Find all minimum cuts (cactus representation)
./build/mincut_parallel network.graph cactus

# Multiterminal cut (NP-hard, branch-and-reduce)
./build/multiterminal_cut network.graph -k 4

When installed via Homebrew, use viecut_mincut, viecut_mincut_parallel, etc. directly.

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Executables

Binary	Parallel	Description
mincut	mincut_parallel	Minimum cut with choice of algorithm
multiterminal_cut		Branch-and-reduce multiterminal cut (MPI)
kcore	kcore_parallel	k-core decomposition
mincut_contract	mincut_contract_parallel	Minimum cut with random edge contraction
mincut_recursive	mincut_recursive_parallel	Recursive minimum cut on largest SCC

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Command Line Usage

./build/mincut [options] <graph-file> <algorithm>
./build/mincut_parallel [options] <graph-file> <algorithm>

Algorithms

Sequential:

Algorithm	Flag	Description
VieCut	vc	Fast heuristic, near-optimal in practice
Nagamochi-Ono-Ibaraki	noi	Classic exact algorithm
Karger-Stein	ks	Randomized contraction
Matula	matula	(2+e)-approximation
Padberg-Rinaldi	pr	Contraction rules
Cactus	cactus	Find all minimum cuts

Parallel:

Algorithm	Flag	Description
Inexact	inexact	Parallel VieCut heuristic
Exact	exact	Parallel exact minimum cut
Cactus	cactus	Parallel cactus of all minimum cuts

Options

Option	Description	Default
-p <int>	Number of processors (parallel only)	all
-i <int>	Number of iterations	1
-q <type>	Priority queue: bqueue, bstack, heap	bqueue
-s	Compute and save the cut	off
-o <file>	Output file for the cut (requires -s)
-b	Find most balanced minimum cut (cactus only, requires -s)	off
-l	Disable priority queue limiting	off

Examples

# Parallel exact minimum cut with 8 threads, 5 iterations
./build/mincut_parallel -p 8 -i 5 network.graph exact

# Save cut to file
./build/mincut -s -o cut.txt network.graph noi

# Most balanced minimum cut
./build/mincut_parallel -s -b network.graph cactus

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Multiterminal Cut

The multiterminal cut separates a set of terminal vertices from each other with minimum total cut weight. For |T|=2 this equals the minimum s-t-cut; for |T|>2 it is NP-hard. VieCut uses a shared-memory parallel branch-and-reduce approach.

./build/multiterminal_cut <graph-file> [options]

Option	Description
-f <file>	Partition file assigning terminals
-t <int>	Add vertex as terminal (repeatable)
-k <int>	Use k highest-degree vertices as terminals
-r <int>	Use r random vertices as terminals
-b <int>	BFS expansion around terminals
-p <int>	Number of threads

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Graph Format

VieCut uses the METIS graph format. Graphs can be unweighted or edge-weighted (format flag 1).

<num_nodes> <num_edges> [format]
<neighbors of node 1> [weights]
<neighbors of node 2> [weights]
...

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Building from Source

Requirements

• C++17 compiler (GCC 7+ or Clang 11+)
• CMake 3.9+
• OpenMP
• MPI (for multiterminal cut)
• TCMalloc (optional, for performance)

Build

git clone --recursive https://github.com/KaHIP/VieCut.git && cd VieCut
mkdir build && cd build
cmake .. -DCMAKE_BUILD_TYPE=Release
make

To build without TCMalloc:

cmake .. -DCMAKE_BUILD_TYPE=Release -DUSE_TCMALLOC=OFF

Sequential and parallel executables are placed in build/.

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Related Projects

Project	Description
KaHIP	Karlsruhe High Quality Graph Partitioning
fpt-max-cut	FPT-based maximum cut solvers

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Licence

VieCut is free software provided under the MIT License. If you publish results using our algorithms, please cite the applicable papers:

@article{DBLP:journals/jea/HenzingerNSS18,
  author    = {Monika Henzinger and Alexander Noe and Christian Schulz and Darren Strash},
  title     = {Practical Minimum Cut Algorithms},
  journal   = {{ACM} J. Exp. Algorithmics},
  volume    = {23},
  year      = {2018},
  doi       = {10.1145/3274662}
}

@inproceedings{DBLP:conf/ipps/HenzingerN019,
  author    = {Monika Henzinger and Alexander Noe and Christian Schulz},
  title     = {Shared-Memory Exact Minimum Cuts},
  booktitle = {2019 {IEEE} International Parallel and Distributed Processing Symposium ({IPDPS})},
  pages     = {13--22},
  publisher = {{IEEE}},
  year      = {2019},
  doi       = {10.1109/IPDPS.2019.00013}
}

@inproceedings{DBLP:conf/esa/HenzingerN0S20,
  author    = {Monika Henzinger and Alexander Noe and Christian Schulz and Darren Strash},
  title     = {Finding All Global Minimum Cuts in Practice},
  booktitle = {28th Annual European Symposium on Algorithms ({ESA} 2020)},
  series    = {LIPIcs},
  volume    = {173},
  pages     = {59:1--59:20},
  publisher = {Schloss Dagstuhl - Leibniz-Zentrum f{\"{u}}r Informatik},
  year      = {2020},
  doi       = {10.4230/LIPIcs.ESA.2020.59}
}

@inproceedings{DBLP:conf/alenex/HenzingerN022,
  author    = {Monika Henzinger and Alexander Noe and Christian Schulz},
  title     = {Practical Fully Dynamic Minimum Cut Algorithms},
  booktitle = {Proceedings of the 24th Symposium on Algorithm Engineering and Experiments ({ALENEX} 2022)},
  pages     = {13--26},
  publisher = {{SIAM}},
  year      = {2022},
  doi       = {10.1137/1.9781611977042.2}
}

@inproceedings{DBLP:conf/alenex/HenzingerN020,
  author    = {Monika Henzinger and Alexander Noe and Christian Schulz},
  title     = {Shared-Memory Branch-and-Reduce for Multiterminal Cuts},
  booktitle = {Proceedings of the 22nd Symposium on Algorithm Engineering and Experiments ({ALENEX} 2020)},
  pages     = {42--55},
  publisher = {{SIAM}},
  year      = {2020},
  doi       = {10.1137/1.9781611976007.4}
}

@inproceedings{DBLP:conf/acda/HenzingerN021,
  author    = {Monika Henzinger and Alexander Noe and Christian Schulz},
  title     = {Faster Parallel Multiterminal Cuts},
  booktitle = {Proceedings of the 2021 {SIAM} Conference on Applied and Computational Discrete Algorithms ({ACDA} 2021)},
  pages     = {100--110},
  publisher = {{SIAM}},
  year      = {2021},
  doi       = {10.1137/1.9781611976830.10}
}