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An efficient real-time implementation of digital filtering algorithms using a multiprocessor system in a ring network is investigated. This method is based on a parallel block processing approach, where a continuously supplied input data is divided into blocks, and the blocks are processed concurrently by being assigned to each processor in the system. This approach requires only a simple interconnection network and reduces significantly the number of communications among the processors, making the system easily expandable and highly efficient. In addition, various digital signal processing algorithms can be implemented on the same multiprocessor system. The data dependency of the blocks to be processed concurrently brings on dependency problems between the processors. A systematic scheduling method has been developed by using a precedence graph for the analysis of the dependency relation. Methods for solving the dependency problems between the processors are also investigated. Implementation procedures and results for FIR, recursive, and adaptive filtering algorithms are illustrated.
Index Termsrecursive filtering algorithms; digital filtering algorithms; parallel block processing;multiprocessor system; ring network; interconnection network; digital signal processingalgorithms; data dependency; scheduling method; precedence graph; dependencyrelation; FIR; adaptive filtering algorithms; computerised signal processing; digital filters; filtering theory; prediction theory; multiprocessor interconnection networks; parallel algorithms

S. Mitra, W. Sung and B. Jeren, "Multiprocessor Implementation of Digital Filtering Algorithms Using a Parallel Block Processing Method," in IEEE Transactions on Parallel & Distributed Systems, vol. 3, no. , pp. 110-120, 1992.
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