![]() Image Processing on FPGAįPGA (Field Program Gate Array) is a specialized reconfigurable hardware which could be also utilized for fast image and video processing. File size will increase a little bit, but we will get an opportunity to accelerate JPEG decoding. We can prepare images for future batching by utilizing the same subsampling, quantization tables and Huffman tables. Most of the time in the pipeline is spent on JPEG Decoding, so we could implement batch just for JPEG decoding. It means that we have to process these algorithms sequentially, though still there is a possibility to get a boost from batch mode. That pipeline consists of different algorithms and we could hardly implement batch processing here for the whole pipeline, as soon as final dimensions are different, images could have different subsampling, individual quantization tables and Huffman tables. Image processing pipeline for JPEG Resize on-demand That idea about on-demand resize for JPEG images is not new and it has already been implemented in several internet services on CPU, GPU and FPGA. In that case we need to store at datacenter just one original picture which will be processed according to individual request parameters. #Fast image resize fullTo cut the expences on storage and to respond to user faster, we can resize JPEG images in realtime according to necessary dimensions to accomplish full match with the requirements of user’s device. Such an approach can’t match desired image resolution exactly. The simplest approach is to store the same JPEG picture at several different resolutions and to send an image which is slightly bigger at each request. That’s why companies spend quite a lot on storages for these pictures and on hardware/software for image processing. Total number of JPEGs in the world is absolutely huge and it’s significantly increasing every day. Server and storage performance is not enoughĪs a task for performance and latency comparison for FPGA vs GPU at image processing, we will consider JPEG Resize on-demand which is widely utilized in web applications.Huge consumption of computational and storage resources.Customers demand instant access to the resource (reduced latency).Users strive to better viewing experience.User devices have higher resolution in capture and display.Users generate more images and video data every day.Images for social networks, image social platforms, cloud albums, photo hosting centers.Many companies are handling huge volumes of images in their data centers: Internet traffic is increasing by ~25% annually (according to white paper from CISCO, see below) and images take considerable part of that data. ![]()
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