{
  "id": 379377,
  "title": "Reading images on GPU",
  "url": "/competitions/nfl-player-contact-detection/discussion/379377",
  "author_name": "",
  "post_date": "2023-01-19T10:58:08.261892Z",
  "votes": 2,
  "comment_count": 2,
  "views": 0,
  "content": "<p>Hello guys, Is there any efficent way to read images to gpu and do all image operations on Gpu? Or doing it on cpu is better?</p>",
  "messages": [
    {
      "id": "2106786",
      "postDate": "01/19/2023 10:58:08",
      "content": "<p>Hello guys, Is there any efficent way to read images to gpu and do all image operations on Gpu? Or doing it on cpu is better?</p>",
      "rawMarkdown": "Hello guys, Is there any efficent way to read images to gpu and do all image operations on Gpu? Or doing it on cpu is better?",
      "votes": null
    },
    {
      "id": "2107566",
      "postDate": "01/19/2023 21:36:00",
      "content": "<blockquote>\n  <p>DALI addresses the problem of the CPU bottleneck by offloading data preprocessing to the GPU. Additionally, DALI relies on its own execution engine, built to maximize the throughput of the input pipeline. Features such as prefetching, parallel execution, and batch processing are handled transparently for the user.</p>\n</blockquote>\n<p>See: <a href=\"https://docs.nvidia.com/deeplearning/dali/user-guide/docs/\" target=\"_blank\">https://docs.nvidia.com/deeplearning/dali/user-guide/docs/</a></p>",
      "rawMarkdown": ">DALI addresses the problem of the CPU bottleneck by offloading data preprocessing to the GPU. Additionally, DALI relies on its own execution engine, built to maximize the throughput of the input pipeline. Features such as prefetching, parallel execution, and batch processing are handled transparently for the user.\n\nSee: https://docs.nvidia.com/deeplearning/dali/user-guide/docs/",
      "votes": null
    },
    {
      "id": "2107568",
      "postDate": "01/19/2023 21:37:36",
      "content": "<p>Thank you!</p>",
      "rawMarkdown": "Thank you!",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 2107566,
      "author_name": "aliabdin1",
      "author_url": "",
      "post_date": "01/19/2023 21:36:00",
      "content": "<blockquote>\n  <p>DALI addresses the problem of the CPU bottleneck by offloading data preprocessing to the GPU. Additionally, DALI relies on its own execution engine, built to maximize the throughput of the input pipeline. Features such as prefetching, parallel execution, and batch processing are handled transparently for the user.</p>\n</blockquote>\n<p>See: <a href=\"https://docs.nvidia.com/deeplearning/dali/user-guide/docs/\" target=\"_blank\">https://docs.nvidia.com/deeplearning/dali/user-guide/docs/</a></p>",
      "votes": null,
      "replies": [
        {
          "id": 2107568,
          "author_name": "dominikmikowski",
          "author_url": "",
          "post_date": "01/19/2023 21:37:36",
          "content": "<p>Thank you!</p>",
          "votes": null,
          "replies": []
        }
      ]
    }
  ],
  "raw_markdown_by_id": {
    "2106786": "Hello guys, Is there any efficent way to read images to gpu and do all image operations on Gpu? Or doing it on cpu is better?",
    "2107566": ">DALI addresses the problem of the CPU bottleneck by offloading data preprocessing to the GPU. Additionally, DALI relies on its own execution engine, built to maximize the throughput of the input pipeline. Features such as prefetching, parallel execution, and batch processing are handled transparently for the user.\n\nSee: https://docs.nvidia.com/deeplearning/dali/user-guide/docs/",
    "2107568": "Thank you!"
  },
  "source": "meta"
}