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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 13055 available papers

The proportion of papers (hgpu.org)nVidia (80%)Not specified (6%)AMD (8%)FPGA (6%)Intel Xeon Phi (0%)

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 platforms200420092014201920242026 YTD17260ALLnVidiaFPGAAMD

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

Papers using established GPU platforms200420092014201920242026 YTD11930CUDAOpenCL

Full-history use of established GPU platforms. The final year is year to date.

Papers using emerging GPU platforms200420092014201920242026 YTD380HIPTritonSYCLROCmoneAPI

Full-history use of emerging GPU platforms. A separate scale makes newer platforms visible.

Number of papers based on NVIDIA accelerators202020252026 YTD670nVidia H100nVidia H200nVidia B200nVidia GB200nVidia A100Tesla V100

Full-history use of NVIDIA data-centre accelerators.

Papers based on AMD accelerators202020252026 YTD160AMD Radeon Instinct MI100AMD Radeon Instinct MI250XAMD Radeon Instinct MI300XAMD Radeon Instinct MI325XAMD Radeon Instinct MI350X

Full-history use of AMD data-centre accelerators.

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