8128

The multi-GPU System with ExpEther

Shimpei Nomura, Tetsuya Nakahama, Junichi Higuchi, Jun Suzuki, Takashi Yoshikawa, Hideharu Amano
Graduate School of Science and Technology, Keio University, 3-14-1 Hiyoshi Kouhoku-ku Yokohama, Kanagawa 223-8522, Japan
International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA’12), 2012
@article{nomura2012multi,

   title={The multi-GPU System with ExpEther},

   author={Nomura, S. and Nakahama, T. and Higuchi, J. and Suzuki, J. and Yoshikawa, T. and Amano, H.},

   year={2012}

}

Download Download (PDF)   View View   Source Source   

386

views

Clusters using multiple GPUs have been already widespread to build a high performance computer economically. However, since the number of plugged GPUs into a CPU is limited, such clusters are consisting of multiple host PCs each of which has a few GPUs. This conventional multi-GPU cluster requires programmers to learn parallel programming skills for controlling communication between nodes as well as GPU programming. In order to show the illusion that a large number of GPUs to a single host, a multi-GPU system with ExpEther is proposed. The multi-GPU system allows interconnecting a single host PC and multiple GPUs by ExpEther which extends PCIe interface to Ethernet. Execution of the application program with two to six GPUs achieved 1.99, 2.96, 3.92, 4.83 and 5.14 times speedup at most, as those with a single GPU. Also, the influence of the bandwidth of the network used in the multi-GPU system is evaluated quantatively.
VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

* * *

* * *

Like us on Facebook

HGPU group

197 people like HGPU on Facebook

Follow us on Twitter

HGPU group

1341 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: nVidia GeForce GTX 560 Ti 2GB, 822MHz
  • 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: nVidia CUDA Toolkit 6.5.14, AMD APP SDK 3.0
Node 2
  • GPU device 0: AMD/ATI Radeon HD 7970 3GB, 1000MHz
  • GPU device 1: AMD/ATI Radeon HD 5870 2GB, 850MHz
  • CPU: Intel Core i7-2600 @ 3.4GHz
  • RAM: 16GB
  • OS: OpenSUSE 12.2
  • SDK: AMD APP SDK 3.0

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: