Abstract:
Network motif discovery, community detection, and frequent subgraph mining require subgraph enumeration. Recent works parallelize subgraph enumeration using GPUs to accelerate execution. Set intersection operations take up to 95% of the processing time in these parallel schemes.
Unsurprisingly, 99 percent of these operations are redundant, meaning they evaluate the same set of vertices. This article salvages and recycles such operations to avoid repeated computation. Our solution is two-phased.
We first create a reusable plan to assess reuse potential. A new reuse discovery mechanism finds available results to avoid redundant computation.
The plan produces subgraph enumeration results in the second phase. A new reusable parallel search strategy efficiently stores and retrieves set intersection results in this processing. Our GPU implementation shows up to 5 times speedups over state-of-the-art GPU solutions.
Note: Please discuss with our team before submitting this abstract to the college. This Abstract or Synopsis varies based on student project requirements.
Did you like this final year project?
To download this project Code with thesis report and project training... Click Here
