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https://hdl.handle.net/2142/79000
Description
Title
Accelerating Graph Partitioning on Modern GPUs
Author(s)
Sun, Chenguang
Contributor(s)
Hwu, Wen-Mei W.
Issue Date
2015-05
Keyword(s)
graph partitioning
parallel computation
GPU
Abstract
The graph partitioning problem is critical to many traditional applications
such as work balancing in distributed computing systems, layout mapping
for VLSI designs, and more. Recent emergence of big data sets makes graph
partitioning even more useful to problems that are larger than ever before,
including ranking of web pages, identification and analysis of social communities,
and many other data mining applications. Graph partitioning algorithms
have high computing costs, and processing such massive graphs calls
for greater performance. This study reviews previous work on graph partitioning
algorithms, and discusses the possibility of accelerating them on
GPUs.
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