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Parallel Scalability in Speech Recognition
Cited 26 time in
Web of Science
Cited 47 time in Scopus
- Authors
- Issue Date
- 2009-11
- Citation
- IEEE Signal Processing Magazine, vol. 25, no. 6, pp. 124-135
- Abstract
- 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.
- ISSN
- 1053-5888
- Language
- English
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