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Parallel scalability in speech recognition

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8 Author(s)
Kisun You ; Seoul Nat. Univ., Seoul, South Korea ; Jike Chong ; Youngmin Yi ; Gonina, E.
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We propose four application-level implementation alternatives called algorithm styles and construct highly optimized implementations on two parallel platforms: an Intel Core i7 multicore processor and a NVIDIA GTX280 manycore processor. The highest performing algorithm style varies with the implementation platform. On a 44-min speech data set, we demonstrate substantial speedups of 3.4 X on Core i7 and 10.5 X on GTX280 compared to a highly optimized sequential implementation on Core i7 without sacrificing accuracy. The parallel implementations contain less than 2.5% sequential overhead, promising scalability and significant potential for further speedup on future platforms.

Published in:

Signal Processing Magazine, IEEE  (Volume:26 ,  Issue: 6 )