12683

Parallel Graph Mining with GPUs

Robest Kessl, Nilothpal Talukder, Pranay Anchuri, Mohammed J. Zaki
Czech Technical University, Prague, Czech Republic
JMLR: Workshop and Conference Proceedings 36:1-16, 2014
@inproceedings{matusevich2014clustering,

   title={A Clustering Algorithm Merging MCMC and EM Methods Using SQL Queries},

   author={Matusevich, David and Ordonez, Carlos},

   booktitle={Proceedings of the 3rd International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications},

   pages={61–76},

   year={2014}

}

Download Download (PDF)   View View   Source Source   

192

views

Frequent graph mining is an important though computationally hard problem because it requires enumerating possibly an exponential number of candidate subgraph patterns, and checking their presence in a database of graphs. In this paper, we propose a novel approach for parallel graph mining on GPUs, which have emerged as a relatively cheap but powerful architecture for general purpose computing. However, the thread-model for GPUs is different from that of CPUs, which makes the parallelization of graph mining algorithms on GPUs a challenging task. We investigate the major challenges for GPU-based graph mining. We perform extensive experiments on several real-world and synthetic datasets, achieving speedups up to 9 over the sequential algorithm.
VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

* * *

* * *

Like us on Facebook

HGPU group

151 people like HGPU on Facebook

Follow us on Twitter

HGPU group

1252 peoples are following HGPU @twitter

* * *

Free GPU computing nodes at hgpu.org

Registered users can now run their OpenCL application at hgpu.org. We provide 1 minute of computer time per each run on two nodes with two AMD and one nVidia graphics processing units, correspondingly. There are no restrictions on the number of starts.

The platforms are

Node 1
  • GPU device 0: AMD/ATI Radeon HD 5870 2GB, 850MHz
  • GPU device 1: AMD/ATI Radeon HD 6970 2GB, 880MHz
  • CPU: AMD Phenom II X6 @ 2.8GHz 1055T
  • RAM: 12GB
  • OS: OpenSUSE 13.1
  • SDK: AMD APP SDK 2.9
Node 2
  • GPU device 0: AMD/ATI Radeon HD 7970 3GB, 1000MHz
  • GPU device 1: nVidia GeForce GTX 560 Ti 2GB, 822MHz
  • CPU: Intel Core i7-2600 @ 3.4GHz
  • RAM: 16GB
  • OS: OpenSUSE 12.2
  • SDK: nVidia CUDA Toolkit 6.0.1, AMD APP SDK 2.9

Completed OpenCL project should be uploaded via User dashboard (see instructions and example there), compilation and execution terminal output logs will be provided to the user.

The information send to hgpu.org will be treated according to our Privacy Policy

HGPU group © 2010-2014 hgpu.org

All rights belong to the respective authors

Contact us: