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6. Mai 2014 · Cliff Woolley is a senior developer technology engineer with NVIDIA. He received his master's degree in Computer Science from the University of Virginia in 2003, where he was among the earliest academic researchers to explore the use of GPUs for general purpose computing.
View Cliff Woolley’s profile on LinkedIn, a professional community of 1 billion members. Experience: NVIDIA · Location: San Jose, California, United States · 12 connections on LinkedIn.
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3. Okt. 2014 · cuDNN: Efficient Primitives for Deep Learning. Sharan Chetlur, Cliff Woolley, Philippe Vandermersch, Jonathan Cohen, John Tran, Bryan Catanzaro, Evan Shelhamer. We present a library of efficient implementations of deep learning primitives.
1. Dez. 2014 · Cliff Woolley (NVIDIA) Philippe Vandermersch (NVIDIA) Jonathan Cohen (NVIDIA) John Tran (NVIDIA) Bryan Catanzaro (Baidu) Evan Shelhamer (UC Berkeley) Publication Date. Monday, December 1, 2014. Published in. Deep Learning and Representation Learning Workshop (NIPS2014) Research Area. Artificial Intelligence and Machine Learning. External Links.
Chapter 35. GPU Program Optimization. Cliff Woolley. University of Virginia. As GPU programmability has become more pervasive and GPU performance has become almost irresistibly appealing, increasing numbers of programmers have begun to recast applications of all sorts to make use of GPUs.
Forked from mjpost/sacrebleu. Reference BLEU implementation that auto-downloads test sets and reports a version string to facilitate cross-lab comparisons. Python. Something went wrong, please refresh the page to try again. If the problem persists, check the GitHub status page or contact support . cliffwoolley has 18 repositories available.
Sharan Chetlur, Cliff Woolley, Philippe Vandermersch, Jonathan Cohen, John Tran, Bryan Catanzaro, Evan Shelhamer: cuDNN: Efficient Primitives for Deep Learning. CoRR abs/1410.0759 (2014) 2000 – 2009. see FAQ. What is the meaning of the colors in the pu ...
