2602

CUDASA: Compute Unified Device and Systems Architecture

M. Strengert, C. Muller, C. Dachsbacher, and T. Ertl
Visualization Research Center (VISUS), University of Stuttgart
Eurographics Symposium on Parallel Graphics and Visualization (2008)
@conference{strengert2008cudasa,

   title={CUDASA: Compute unified device and systems architecture},

   author={Strengert, M. and M{\”u}ller, C. and Dachsbacher, C. and Ertl, T.},

   booktitle={EG Symp. Parallel Graph. Vis., S},

   pages={49–56},

   year={2008}

}

Download Download (PDF)   View View   Source Source   

324

views

We present an extension to the CUDA programming language which extends parallelism to multi-GPU systems and GPU-cluster environments. Following the existing model, which exposes the internal parallelism of GPUs, our extended programming language provides a consistent development interface for additional, higher levels of parallel abstraction from the bus and network interconnects. The newly introduced layers provide the key features specific to the architecture and programmability of current graphics hardware while the underlying communication and scheduling mechanisms are completely hidden from the user. All extensions to the original programming language are handled by a self-contained compiler which is easily embedded into the CUDA compile process. We evaluate our system using two different sample applications and discuss scaling behavior and performance on different system architectures.
VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

* * *

* * *

Like us on Facebook

HGPU group

167 people like HGPU on Facebook

Follow us on Twitter

HGPU group

1275 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: