Dynamic Memory Model based Optimization of Scalar and Vector Quantizer Encoder
Abstract: The rapid progress of computers and today's heterogeneous computing environment means computation-intensive signal processing algorithms must be optimized for performance in a machine dependent fashion. In this paper, we present design and analysis of an automated algorithm optimizer for scalar and vector quantizer encoders. Using a dynamic memory model, the optimal computation-memory tradeoff is exploited to minimize the encoding time. Experiments show our proposed optimized algorithm has marked improvements over existing techniques.