Skip to main content
USENIX
  • Conferences
  • Students
Sign in

connect with us


  •  Twitter
  •  Facebook
  •  LinkedIn
  •  Google+
  •  YouTube

twitter

Tweets by @usenix

usenix conference policies

  • Event Code of Conduct
  • Conference Network Policy
  • Statement on Environmental Responsibility Policy

You are here

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

connect with us

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,
}
Download

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
  • Log in or    Register to post comments

© USENIX

  • Privacy Policy
  • Contact Us