GraphMat graph analytics framework
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Updated
Jan 25, 2023 - C++
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.
Probably the first scalable and open source triangle count based on each edge, on scala and spark for every Big Dataset. (Louvain)
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.
Graph Processing Framework that supports || OpenMP || CAPI
MPI implementation of a parallel algorithm for finding the exact number of triangles in massive networks
Drawing shapes are very easy, like <circle></circle> <square></square>
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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