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Proceedings Paper

Motion estimation for H.264/AVC on multiple GPUs using NVIDIA CUDA
Author(s): Bart Pieters; Charles F. Hollemeersch; Peter Lambert; Rik Van de Walle
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Paper Abstract

To achieve the high coding efficiency the H.264/AVC standard offers, the encoding process quickly becomes computationally demanding. One of the most intensive encoding phases is motion estimation. Even modern CPUs struggle to process high-definition video sequences in real-time. While personal computers are typically equipped with powerful Graphics Processing Units (GPUs) to accelerate graphics operations, these GPUs lie dormant when encoding a video sequence. Furthermore, recent developments show more and more computer configurations come with multiple GPUs. However, no existing GPU-enabled motion estimation architectures target multiple GPUs. In addition, these architectures provide no early-out behavior nor can they enforce a specific processing order. We developed a motion search architecture, capable of executing motion estimation and partitioning for an H.264/AVC sequence entirely on the GPU using the NVIDIA CUDA (Compute Unified Device Architecture) platform. This paper describes our architecture and presents a novel job scheduling system we designed, making it possible to control the GPU in a flexible way. This job scheduling system can enforce real-time demands of the video encoder by prioritizing calculations and providing an early-out mode. Furthermore, the job scheduling system allows the use of multiple GPUs in one computer system and efficient load balancing of the motion search over these GPUs. This paper focuses on the execution speed of the novel job scheduling system on both single and multi-GPU systems. Initial results show that real-time full motion search of 720p high-definition content is possible with a 32 by 32 search window running on a system with four GPUs.

Paper Details

Date Published: 2 September 2009
PDF: 12 pages
Proc. SPIE 7443, Applications of Digital Image Processing XXXII, 74430X (2 September 2009); doi: 10.1117/12.825995
Show Author Affiliations
Bart Pieters, Univ. Gent (Belgium)
Charles F. Hollemeersch, Univ. Gent (Belgium)
Peter Lambert, Univ. Gent (Belgium)
Rik Van de Walle, Univ. Gent (Belgium)


Published in SPIE Proceedings Vol. 7443:
Applications of Digital Image Processing XXXII
Andrew G. Tescher, Editor(s)

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