Abstract
We present a massively parallel version of a full search vector quantization and its application in the development of an audio-visual speech recognition system. The parallel implementation reduced the worst case runtime of (estimated) 80–100 hours on a 10 MFLOP SPARC to less then 2 hours on a 2.4 GFOLP MasPar MP2216. This demonstrates how the use of parallel computers reduces product development time and leads to a more mature design by allowing for more extensive experimentation with different data sets.
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References
Allen Gersho, Robert M. Gray, Vector Quantization and Signal Compression Kluwer Academic Publishers, Boston, 1992
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© 1994 Springer-Verlag Berlin Heidelberg
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Lukowicz, P., Schiffers, J., Cober, R. (1994). A massively parallel implementation of the full search vector quantization algorithm. In: Gentzsch, W., Harms, U. (eds) High-Performance Computing and Networking. HPCN-Europe 1994. Lecture Notes in Computer Science, vol 796. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0020410
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DOI: https://doi.org/10.1007/BFb0020410
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