Massively parallel algorithm for vector quantization

Journal ArticleThis paper is concerned with the parallel implementation of a vector quantizer system on Maspar MP-2, a single-instruction, multiple-data (SIMD) massively parallel computer. A vector quantizer (VQ) consists of two mappings: an encoder and a decoder. The encoder assigns to each input vector the index of the codevector that is closest to it. The decoder uses this index to reconstruct the signal. In our work, we used the Euclidean distortion measure to find the codevector closest to each input vector. The work described in this paper used a Maspar MP-2216 located at the Goddard Space Flight Center, Greenbelt, Maryland. This system has 16,384 processor elements (PES) arranged in a rectangular array of 128 x 128 nodes