![]() Note that at this time they use the GAPBS CLI, use -h for more information on usage. The binaries corresponding to various combinations will be placed in a subdirectory called gapbs. To build the original GAPBS benchmarks with compressed graphs, enable the CMake option BUILD_GAPBS_BENCHMARKS and build the project. Set the debug flag DEBUG_WITH_SANITIZERS=ON to enable compilation with sanitizers in debug builds. (Installed by default on Debian-based distributions.) Individual make targets for the modules are created to facilitate faster development.įor debugging builds it's recommended to also install libasan and libusan if they aren't already part of your installation. You will now find the benchmark binaries in a subdirectory bin of the current build directory.$ make -j4 (where 4 is the number of threads to build the code) ![]() for the debugging build, which is recommended during development since it enables compiler sanitizers and bounds checking (in some places), change Release to Debug.Here and in the rest of the documentation we refer to the path of the Git repository as $REPO. scripts: Some simple postprocessing scripts, written in Bash and Python.examples: Examples accompanying the documentation.third_party: Several third-party libraries, see top-level README for more information.sets: Set representations and operations.permuters: Graph neighborhood permuters that can be applied to neighborhoods prior to computation.coders: Graph neighborhood encoders and decoders for composable compression.common: Functionality intended to be reused across GMS providing essential benchmark infrastructure.vertex_similarity: Implementations of vertex similarity functions.triangle_count: Set-based triangle counting.maximal_clique_enum: Implementation of Bron-Kerbosch algorithm and extensions.link_prediction: Vertex similarity based link prediction, and robust methods to assess its performance.k_clique_star_list: Implementation of k-clique-star listing.k_clique_count: Simple unoptimized version of clique counting, that is implemented with sets.set_based: Algorithms implemented with a set-based approach, i.e.subgraphiso: Implementation of Glasgow and VF2 subgraph isomorphism algorithms.k_clique_list: Implementation of k-clique listing algorithm of Danisch et al.coloring: Implementations of various graph coloring algorithms.non_set_based: Algorithms implemented with a non set-based approach, i.e.preprocessing: Vertex ordering implementations, which can be used as preprocessing for other algorithms.algorithms: Algorithm implementations and benchmarks.Bin/maximal_clique_enum_bron_kerbosch -g uniform 10 Project structure
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