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CUDA-level Performance with Python-level Productivity for Gaussian Mixture Model Applications

H. Cook, University of California, Berkeley

E. Gonina, University of California, Berkeley

S. Kamil, University of California, Berkeley

G. Friedland, International Computer Science Institute

D. Patterson, University of California, Berkeley

A. Fox, University of California, Berkeley

BibTeX
@inproceedings {266869,
author = {H. Cook and E. Gonina and S. Kamil and G. Friedland and D. Patterson and A. Fox},
title = {{CUDA-level} Performance with Python-level Productivity for Gaussian Mixture Model Applications},
booktitle = {3rd USENIX Workshop on Hot Topics in Parallelism (HotPar 11)},
year = {2011},
address = {Berkeley, CA},
url = {https://www.usenix.org/conference/hotpar-11/cuda-level-performance-python-level-productivity-gaussian-mixture-model},
publisher = {USENIX Association},
month = may
}
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Links

Paper: 
http://www.usenix.org/events/hotpar11/tech/final_files/Cook.pdf
Paper (HTML): 
http://www.usenix.org/events/hotpar11/tech/techAbstracts.html#Cook
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