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 6959 available papers
Hardware percentage of all papers posted on hgpu.org. Unknown platforms include all other parallel processing units (Cell processors, FPGA etc.) or information about the platform is not available.
The number of the papers per year describing the applications developed for various graphics processing units.
The number of the papers per year describing the applications developed with the use of the CUDA, OpenGL, DrectX, Brook and OpenCL programming languages.
The number of the papers per year describing the applications performed on various nVidia GPU.
Most viewed papers (last 30 days)
- Graphics Programming on the Web WebCL Course Notes
- Simulating the universe with GPU-accelerated supercomputers: n-body methods, tests, and examples
- Secrets from the GPU
- Implementations of the FFT algorithm on GPU
- Fluid Motion Modelling Using Vortex Particle Method on GPU
- Adding GPU Computing to Computer Organization Courses
- libWater: Heterogeneous Distributed Computing Made Easy
- Fast Implementation of Scale Invariant Feature Transform Based on CUDA
- Faster Upper Body Pose Estimation and Recognition Using CUDA
- Analyzing Locality of Memory References in GPU Architectures
