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U.S. Department of Energy
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Vector and multiprocessor implementation of digital filtering algorithms

Thesis/Dissertation ·
OSTI ID:6445756

The efficient implementation of digital-filtering algorithms using parallel computer systems is investigated. This study presents a new direction for the parallel implementation by enabling an efficient use of a large number of processors. Parallel computation of linear recursive equations is treated first because these equations are used for describing many digital-filtering algorithms. These equations bring dependency problems in the computation of multiple output samples at the same time due to the feedback structure. A new method is developed to overcome these problems. With regard to vector-processor implementations, vectorization methods are reviewed, and applied to the implementation of digital-filtering algorithms. In particular, recursive and adaptive filtering algorithms are implemented very efficiently by applying the developed parallel computation method for recursive equations. A multiprocessor implementation method which only requires a ring network for interprocessor communication is studied. The method divides input data into blocks, and assigns a block of data to each processor in rotation. The final area is devoted to the architectural design of a VLSI single-chip processor. This processor is equipped with pipelined functional units for processing vector operations efficiently.

Research Organization:
California Univ., Santa Barbara (USA)
OSTI ID:
6445756
Country of Publication:
United States
Language:
English