Mapping real-time motion estimation type algorithms to memory efficient,programmable multi-processor architectures |
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Institution: | 1. Amity School of Engineering and Technology, Amity University Madhya Pradesh, Gwalior, India;2. Big Data and Machine Learning Lab, South Ural State University (National Research University), Chelyabinsk, Russian Federation |
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Abstract: | In this paper, an architectural template is presented, which is able to execute the full search motion estimation algorithm or other similar video or image processing algorithms in real time. The architecture is based on a set of programmable video signal processors (VSP's). It is also possible to integrate the processor cores and their local memories on a (set of) chip(s). Due to the programmability, the system is very flexible and can be used for emulation of other similar block-oriented local-neighborhood algorithms. The architecture can be easily divided into several partitions, without data-exchange between partitions. Special attention is paid to memory size and transfer optimization, which are dominant factors for both area and power cost. The trade-offs and techniques used to arrive at these solutions are explained in detail. It is shown that careful optimizations can lead to large savings in memory size (up to 66%) and bandwidth requirements (up to a factor of 4) compared to a straightforward solution. |
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