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29 January 2007 Resource estimation methodology for multimedia applications
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Proceedings Volume 6504, Multimedia Computing and Networking 2007; 65040L (2007)
Event: Electronic Imaging 2007, 2007, San Jose, CA, United States
Reducing the product development cycle time is one of the most important and challenging problems faced by the industry today. As the functionality and complexity of devices increases, so does the time required to design, test, and develop the devices. Developing products rapidly in the face of this increasing complexity requires new methodologies and tools. This paper presents a methodology for estimating the resources consumed by a video decoder. The proposed methodology enables resource estimation based on high level user requirements. Component architecture for a H.264 video decoder is developed to enable design space exploration. The resources required to decode H.264 video are estimated based on a measure of the complexity of the H.264 bitstreams and the target architecture. The proposed approach is based on the hypothesis that the complexity of a H.264 video bitstream significantly influences resource consumption and the complexity of a bitstream can thus be used to determine resource estimation. The bitstream complexity is characterized to capture the data dependencies using a process called Bitstream Abstraction. The decoder is componentized and component level resource requirements determined in a process called Decoder Abstraction. The proposed methodology uses Bitstream Abstraction together with Decoder Abstraction to estimate resource requirements. A component model for the H.264 video decoder is developed. Resources consumed by each component are determined using the VTune performance analyzer. These resource estimates and video bitstream complexity are used in developing a parametric model for resource estimation based on bitstream complexity. The proposed methodology enables high level resource estimation for multimedia applications without a need for extensive and time consuming simulations.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hari Kalva, Ravi Shankar, Tuhina Patel, and Camilo Cruz "Resource estimation methodology for multimedia applications", Proc. SPIE 6504, Multimedia Computing and Networking 2007, 65040L (29 January 2007);

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