In the past decade, Graphics Processing Units have played an important role in the field of
high-performance computing and they still advance new fields such as IoT, autonomous …

Subgraph matching finds all distinct isomorphic embeddings of a query graph on a data
graph. For large graphs, current solutions face the scalability challenge due to expensive …

There is a growing need to perform a diverse set of real-time analytics (batch and stream
analytics) on evolving graphs to deliver the values of big data to users. The key requirement …

High-performance implementations of graph algorithms are challenging to implement on
new parallel hardware such as GPUs because of three challenges:(1) the difficulty of coming …

There is growing interest in graph pattern mining (GPM) problems such as motif counting.
GPM systems have been developed to provide unified interfaces for programming …

Subgraph matching is a fundamental task in many applications which identifies all the
embeddings of a query pattern in an input graph. Compilation-based subgraph matching …

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 …

A fundamental problem in large-scale network analysis is finding and enumerating basic
graph motifs. Graph motifs that represent the building blocks of certain networks can reveal …

With high computation power and memory bandwidth, graphics processing units (GPUs)
lend themselves to accelerate data-intensive analytics, especially when such applications fit …