Performance evaluation of H.264/AVC decoding and visualization using the GPU

Abstract

The coding efficiency of the H.264/AVC standard makes the decoding process computationally demanding. This has limited the availability of cost-effective, high-performance solutions. Modern computers are typically equipped with powerful yet cost-effective Graphics Processing Units (GPUs) to accelerate graphics operations. These GPUs can be addressed by means of a 3-D graphics API such as Microsoft Direct3D or OpenGL, using programmable shaders as generic processing units for vector data. The new CUDA (Compute Unified Device Architecture) platform of NVIDIA provides a straightforward way to address the GPU directly, without the need for a 3-D graphics API in the middle. In CUDA, a compiler generates executable code from C code with specific modifiers that determine the execution model. This paper first presents an own-developed H.264/AVC renderer, which is capable of executing motion compensation (MC), reconstruction, and Color Space Conversion (CSC) entirely on the GPU. To steer the GPU, Direct3D combined with programmable pixel and vertex shaders is used. Next, we also present a GPU-enabled decoder utilizing the new CUDA architecture from NVIDIA. This decoder performs MC, reconstruction, and CSC on the GPU as well. Our results compare both GPU-enabled decoders, as well as a CPU-only decoder in terms of speed, complexity, and CPU requirements. Our measurements show that a significant speedup is possible, relative to a CPU-only solution. As an example, real-time playback of high-definition video (1080p) was achieved with our Direct3D and CUDA-based H.264/AVC renderers.

Towards block-based compression of genomic data with random access functionality

“…As a result, a broad range of advanced research topics can be addressed effectively. These research topics include, amongst others: 978-1-4799-7088-9/14/$31.00 ©2014 IEEE GlobalSIP14-Workshop on Genomic Signal Processing and Statistics 2014 • random access functionality; • compressed-domain processing [8]; • stream processing [9]; • adaptive streaming [10]; and • encryption [11]. Interestingly, these research topics can also be studied within the context of genomic data processing.…”

Exploration of Full HD Media Decoding on a Software Defined Radio Baseband Processor

“…Graphics Processing Units (GPUs), which usually consist of hundreds of processing cores, are able to achieve immense parallel computing performance. The deblocking [12], MC [13], [14] algorithms of H.264/AVC have been implemented on the NVIDIA CUDA [15] platform. The representative CGRAs, like REMUS-II and XPP-III have implemented H.264/AVC full HD at 30 fps and 24 fps respectively.…”

Parallel H.264/AVC Motion Compensation for GPUs Using OpenCL

“…Pieter et al [6] employed a similar idea to offload the motion compensation in H.264/AVC onto GPUs using CUDA. However, this strategy requires extra mode-location mapping buffers to indicate the positions of the blocks with the same interpolation mode.…”