Treffer: Research on optimization method of multithreaded computing architecture for large-scale digital media data processing.

In recent years, with the rapid development of information technology, the traditional single-threaded processing method can no longer meet the rapid growth of digital media data volume. In this paper, based on the digital media data processing system based on BS structure, the GPGPU parallel processing architecture is used for optimization. The access efficiency of massive parallel multithreading is ensured by executing a multilevel storage architecture composed of behavior decision unit, branch merge unit and branch recovery stack. The study designs the computational resource pool as well as the storage resource pool to form an infrastructure solution to the data processing problem. The query performance of the digital media data processing system using the GPGPU microarchitecture with multithreaded parallel processing is improved by about 81% and 69% or so compared to the Ocelot and prototype systems, respectively. And the average execution time for performing dynamic data allocation is 5.17s less than that of the original system. It shows that the optimized digital media data processing system has better data processing efficiency. [ABSTRACT FROM AUTHOR]

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