High Throughput Image/Video Codec with Nvidia GPUs
The increasing number of image and video content, and the adoption of 8K resolution and high dynamic range technologies, demand faster and more efficient digital coding solutions to store and transfer these data. State-of-the-art solutions like HEVC or JPEG2000 are widely adopted but their computati...
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| Tipo de recurso: | tesis doctoral |
| Estado: | Versión publicada |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | CBUC, CESCA |
| Repositorio: | TDR. Tesis Doctorales en Red |
| OAI Identifier: | oai:www.tdx.cat:10803/675121 |
| Acceso en línea: | http://hdl.handle.net/10803/675121 |
| Access Level: | acceso abierto |
| Palabra clave: | JPEG2000 CUDA Codec Ciències Experimentals 004 |
| Sumario: | The increasing number of image and video content, and the adoption of 8K resolution and high dynamic range technologies, demand faster and more efficient digital coding solutions to store and transfer these data. State-of-the-art solutions like HEVC or JPEG2000 are widely adopted but their computational requirements pose a challenge even for current hardware. For environments like digital cinema or medical image, specific FPGA boards are used to accelerate image processing without affecting image quality. In the last years, a massive parallel hardware has started to gain attraction: Graphical Processing Units (GPUs). GPUs are massive parallel architectures originally suited for videogames or 3D simulations. In the recent years, their adoption as general purpose devices have allowed to use them as accelerators for a myriad of applications. Algorithms properly adapted to run on GPUs get significant throughput improvements when compared to their CPU implementation. This research focuses on creating an end-to-end codec based on the JPEG2000 standard tailored for GPUs. This thesis proposes five main contributions, all of which have been published in relevant conferences or journals. The first one focuses on the first end-to-end GPU codec version, which can code and decode gray-scale images. The second version includes the implementation of the video engine within the codec, which can process up to two frames simultaneously. The third contribution consists of an in-depth analysis of the end-to-end codec with multiple throughput improvements and the addition of a multi-frame processing approach, which allows to process multiple frames simultaneously when coding video. The fourth contribution proposes the implementation of an improvement to the core coding engine, tested on a CPU version of the end-to-end codec. The last contribution details an in-depth analysis of the improvement presented in the previous paper but implemented in the end-to-end GPU codec, including results with improvements of more than 10× the performance of the best JPEG2000 commercial implementation when processing 4K RGB video. |
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