With the help of the Internet of Things (IoT), an evolving technology, issues may be solved in
the fields of research and engineering without the involvement of a human workforce. It …

Many applications require to learn, mine, analyze and visualize large-scale graphs. These
graphs are often too large to be addressed efficiently using conventional graph processing …

Graph pattern mining (GPM) is a class of algorithms widely used in many real-world
applications in bio-medicine, e-commerce, security, social sciences, etc. GPM is a …

Graph pattern mining (GPM) is a key building block in diverse applications, including
bioinformatics, chemical engineering, social network analysis, recommender systems and …

Graph mining is an emerging application of high importance and also with high complexity,
thus requiring efficient hardware acceleration. Current accelerator designs only utilize …

Truss decomposition is to divide a graph into a hierarchy of subgraphs, or trusses. A
subgraph is ak-truss (k≥ 2) if each edge is in at least k---2 triangles in the subgraph …

Triangle counting is a building block for a wide range of graph applications. Traditional
wisdom suggests that i) hashing is not suitable for triangle counting, ii) edge-centric triangle …

Butterfly counting is an important and costly operation for large bipartite graphs. GPUs are
popular parallel heterogeneous devices and can bring significant performance improvement …

This paper proposes a scheme to reduce big graphs to small graphs. It contracts obsolete
parts, stars, cliques and paths into supernodes. The supernodes carry a synopsis S_Q for …

We present a GPU solution for exact maximal clique enumeration (MCE) that performs a
search tree traversal following the Bron-Kerbosch algorithm. Prior works on parallelizing …