A massively parallel implementation of the full search vector quantization algorithm
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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