As graph analytics often involves compute-intensive operations, GPUs have been
extensively used to accelerate the processing. However, in many applications such as social …

Subgraph isomorphism is a well-known NP-hard problem that is widely used in many
applications, such as social network analysis and querying over the knowledge graph. Due …

Subgraph matching is a basic operation in graph analytics, finding all occurrences of a
query graph Q in a data graph G. A common approach is to first filter out non-candidate …

Hypergraphs are generalizations of graphs where the (hyper) edges can connect any
number of vertices. They are powerful tools for representing complex and non-pairwise …

Due to the inherent hardness of subgraph isomorphism, the performance is often a
bottleneck in various real-world applications. We address this by designing an efficient …

Graph processing on GPUs received much attention in the industry and the academia
recently, as the hardware accelerator offers attractive potential for performance boost …

Graphic processing units (GPUs) have been employed as hardware accelerators for online
analytics. However, multi-way joins, which are common in analytic workloads, are inefficient …

Subgraph matching, as a challenging problem in the graph area, has a wide range of
applications from social networks to computational biology. It refers to finding the …

In this paper, we propose a GPU-efficient subgraph isomorphism algorithm using the
Gunrock graph analytic framework, GSM (Gunrock Subgraph Matching), to compute graph …

Subgraph isomorphism plays a significant role in many applications, such as social
networks and bioinformatics. However, due to the inherent NP-hardness, it becomes …