NOTE: The cuhornet repository is a copy of https://github.com/hornet-gt/hornet that is being maintained by the RAPIDS cugraph team while we use it in our library. We currently only use headers to provide the ktruss implementation.
This library does not currently build. Since we only use headers, we are not maintaining the build processes for this library. We expect to drop support for this entirely in early 2024.
This repository provides the Hornet data structure and algorithms on sparse graphs and matrices.
The document is organized as follows:
- Requirements
- Quick start
- Supported graph formats
- Code Documentation
- Notes
- Reporting bugs and contributing
- Publications
- Hornet Developers
- License
- CUDA toolkit 9 or greater.
- GCC or Clang host compiler with support for C++14. Note, the compiler must be compatible with the related CUDA toolkit version. For more information see CUDA Installation Guide.
- CMake v3.8 or greater.
- 64-bit Operating System (Ubuntu 16.04 or above suggested).
The following basic steps are required to build and execute Hornet:
git clone --recursive https://github.com/hornet-gt/hornet
export CUDACXX=<path_to_CUDA_nvcc_compiler>
cd hornet/build
cmake ..
make -jTo build HornetsNest (algorithms directory):
cd hornetsnest/build
cmake ..
make -jBy default, the CUDA compiler nvcc uses gcc/g++ found in the current
execution search path as host compiler
(cc --version to get the default compiler on the actual system).
To force a different host compiler for compiling C++ files (*.cpp)
you need to set the following environment variables:
CC=<path_to_host_C_compiler>
CXX=<path_to_host_C++_compiler>Note: host .cpp compiler and host side .cu compiler may be different.
The host side compiler must be compatible with the current CUDA Toolkit
version installed on the system
(see CUDA Installation Guide).
The syntax and the input parameters of Hornet are explained in detail in
docs/Syntax.txt. They can also be found by typing ./HornetTest --help.
Hornet supports the following graph input formats:
- Market (.mtx), The University of Florida Sparse Matrix Collection
- Metis (.graph), 10th DIMACS Implementation Challenge
- SNAP (.txt), Stanford Network Analysis Project
- Dimacs9th (.gr), 9th DIMACS Implementation Challenge
- The Koblenz Network Collection (out.< name >), The Koblenz Network Collection
- Network Data Repository (.edges), Network Data Repository
- Binary (.bin)
Hornet directly deduces the graph structure (directed/undirected) from the input file header.
Hornet allows reading the input graph by using a fixed binary format to speed up the file loading.
The binary file is generated by Hornet with the --binary command line option.
The code documentation is located in the docs directory (doxygen html format).
- Hornet has been checked with the following tools to ensure the code quality:
- clang++ v4.0: warnings
- clang-tidy: warnings and code styles
- Hornet has been tested with the following tools: (see
CodeCheck)
If you find any bugs please report them by using the repository (github issues panel). We are also ready to engage in improving and extending the framework if you request new features.
| Algorithm | Static | Dynamic |
|---|---|---|
| (BFS) Breadth-first Search | yes | on-going |
| (SSSP) Single-Source Shortest Path | yes | on-going |
| (CC) Connected Components | yes | on-going |
| (SCC) Strongly Connected Components | to-do | to-do |
| (MST) Minimum Spanning Tree | on-going | to-do |
| (BC) Betweeness Centrality | yes | on-going |
| (PG) Page Rank | yes | yes |
| (TC) Triangle Counting | yes | on-going |
| (KC) Katz Centrality | yes | yes |
| (MIS) Maximal Independent Set | on-going | to-do |
| (MF) Maximum Flow | to-do | to-do |
| (CC) Clustering Coeffient | yes | to-do |
| (ST) St-Connectivity | to-do | to-do |
| (TC) Transitive Closure | to-do | to-do |
| Community Detection | on-going | to-do |
| Temporal Motif Finding | on-going | to-do |
| Sparse Vector-Matrix Multiplication | yes | to-do |
| Jaccard indices | on-going | to-do |
| Energy/Parity Game | on-going | to-do |
- F. Busato, O. Green, N. Bombieri, D. Bader, “Hornet: An Efficient Data Structure for Dynamic Sparse Graphs and Matrices”, IEEE High Performance Extreme Computing Conference (HPEC), Waltham, Massachusetts, 2018 link
- Oded Green, David A. Bader, "cuSTINGER: Supporting dynamic graph algorithms for GPUs", IEEE High Performance Extreme Computing Conference (HPEC), 13-15 September, 2016, Waltham, MA, USA, pp. 1-6. link
- Fox, O. Green, K. Gabert, X. An, D. Bader, “Fast and Adaptive List Intersections on the GPU”, IEEE High Performance Extreme Computing Conference (HPEC), Waltham, Massachusetts, 2018 **HPEC Graph Challenge Finalist **
- O. Green, J. Fox, A. Tripathy, A. Watkins, K. Gabert, E. Kim, X. An, K. Aatish, D. Bader, “Logarithmic Radix Binning and Vectorized Triangle Counting”, IEEE High Performance Extreme Computing Conference (HPEC), Waltham, Massachusetts, 2018 (HPEC Graph Challenge Innovation Award)
- A. van der Grinten, E. Bergamini, O. Green, H. Meyerhenke, D. Bader, “Scalable Katz Ranking Computation in Large Dynamic Graphs”, European Symposium on Algorithms, Helsinki, Finland, 2018
- Oded Green, James Fox, Euna Kim, Federico Busato, Nicola Bombieri, Kartik Lakhotia, Shijie Zhou, Shreyas Singapura, Hanqing Zeng, Rajgopal Kannan, Viktor Prasanna, David A. Bader, "Quickly Finding a Truss in a Haystack", IEEE/Amazon/DARPA Graph Challenge, *Innovation Awards*.
- Devavret Makkar, David A. Bader, Oded Green, Exact and Parallel Triangle Counting in Streaming Graphs, IEEE Conference on High Performance Computing, Data, and Analytics (HiPC), 18-21 December 2017, Jaipur, India, pp. 1-10.
- A. Tripathy, F. Hohman, D.H Chau, O. Green, "Scalable K-Core Decomposition for Static Graphs Using a Dynamic Graph Data Structure", IEEE International Conference on Big Data, Seattle, Washington, 2018 link
Federico Busato, Ph.D. Student, University of Verona (Italy)Oded Green, Researcher, Georgia Institute of TechnologyFederico Busato, Ph.D. Student, University of Verona (Italy)Oded Green, Researcher, Georgia Institute of TechnologyJames Fox, Ph.D. Student, Georgia Institute of Technology : Maximal Independent Set, Temporal Motif FindingDevavret Makkar, Ph.D. Student, Georgia Institute of Technology : Triangle CountingElisabetta Bergamini, Ph.D. Student, Karlsruhe Institute of Technology (Germany) : Katz CentralityEuna Kim, Ph.D. Student, Georgia Institute of Technology : Dynamic PageRank- ...
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