GraphMat graph analytics framework
A Parallel Graphlet Decomposition Library for Large Graphs
The official code for DATE'23 paper <CLAP: Locality Aware and Parallel Triangle Counting with Content Addressable Memory>
OpenMP-based parallel program for counting the number of triangles in a sparse graph
Vertex Ordering to List Triangles: a fast C++ tool for triangle counting or listing in big graphs. See associated paper: https://arxiv.org/abs/2203.04774
OpenGraph is an open-source graph processing benchmarking suite written in pure C/OpenMP.
OpenGraph is an open-source graph processing benchmarking suite written in pure C/OpenMP. Integrated with Sniper simulator.
A distributed algorithm applied to the bitcoin blockchain that allows to create a new representation of the transaction - a clusterized graph that combines all the addresses belonging to the same owner/organization.
Probably the first scalable and open source triangle count based on each edge, on scala and spark for every Big Dataset. (Louvain)
Graph Processing Framework that supports || OpenMP || CAPI
Drawing shapes are very easy, like <circle></circle> <square></square>
MPI implementation of a parallel algorithm for finding the exact number of triangles in massive networks
Implementation of Big Data Analytics Algorithms in Python
High performance triangle counting in large sparse graphs
Distributed Triangle Counting
Count triangles that graph nodes form, in a parallel program.
Fast parallel triangle counting using OpenCilk, OpenMP, and Pthreads
Parallel Kronecker Binary EdgeList (*.bin) To CSR (Lijun Chang's Format: b_adj.bin, b_degree.bin), Graph Statistics: Parallel TC/Core/DODG Analytics
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