Statistics of platform usage

Modern customer video cards that can be used for general purpose (non-graphic) applications are provided mainly by two vendors, nVidia and AMD. The specifications of the manufactured GPU are collected on the Hardware page of hgpu.org. Introduction of the CUDA proramming language for nVidia graphics processing units, which had made GPGPU calculations easier than before, cause appearence of the large number of GPU applications. Some common libraries (e.g. BLAS, FFT) have also been developed for GPU with the use of CUDA. Most of the application reported up to date are realized on nVidia platform. The statistics page provides information about the platforms (hardware and software) on which the works posted on hgpu.org have been performed.


Statistics is based on 9856 available papers

The proportion of papers based on different GPU developers

Hardware percentage of all papers posted on hgpu.org. Unknown platforms include all other parallel processing units (Cell processors, etc.) or information about the platform is not available.

Number of papers for different GPU platforms

The number of the papers per year describing the applications developed for various graphics processing units.

Number of papers for different GPGPU languages

The number of the papers per year describing the applications developed with the use of the CUDA, OpenGL, DrectX, Brook and OpenCL programming languages.

Number of papers based on most popular nVidia GPUs

The number of the papers per year describing the applications performed on various nVidia GPU.

* * *

* * *

Follow us on Twitter

HGPU group

1666 peoples are following HGPU @twitter

Like us on Facebook

HGPU group

338 people like HGPU on Facebook

* * *

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 12.3
  • 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 © 2010-2015 hgpu.org

All rights belong to the respective authors

Contact us: