This repository provides the Hornet data structure and algorithms on sparse graphs and matrices.
The document is organized as follows:
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 -j
To build HornetsNest (algorithms directory):
cd hornetsnest/build
cmake ..
make -j
By 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:
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).
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 |
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 PageRankBSD 3-Clause License
Copyright (c) 2017, Hornet All rights reserved.
Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
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