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1. developer.nvidia.com › blog › authorAuthor: Cliff Woolley | NVIDIA Technical Blog

   developer.nvidia.com › blog › author

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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.

2. www.linkedin.com › in › cliff-woolley-789321145Cliff Woolley - NVIDIA | LinkedIn

   www.linkedin.com › in › cliff-woolley-789321145

   View Cliff Woolley’s profile on LinkedIn, a professional community of 1 billion members. Experience: NVIDIA · Location: San Jose · 12 connections on LinkedIn.

   • Verbindungen: 12
   • Follower: 25

   • Arbeitet für: NVIDIA
   • Standort: San Jose, California, United States

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4. arxiv.org › abs › 1410[1410.0759] cuDNN: Efficient Primitives for Deep Learning -...

   arxiv.org › abs › 1410

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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.

   • Autor: Sharan Chetlur, Cliff Woolley, Philippe Vandermersch, Jonathan Cohen, John Tran, Bryan Catanzaro, Ev...

   • Publish Year: 2014

5. developer.nvidia.com › blog › cuda-pro-tip-improve-nvvpCUDA Pro Tip: Improve NVIDIA Visual Profiler Loading of Large...

   developer.nvidia.com › blog › cuda-pro-tip-improve-nvvp

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   About Cliff Woolley 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. Today he works with developers of high ...

6. arxiv.org › pdf › 1410cuDNN: Efficient Primitives for Deep Learning - arXiv.org

   arxiv.org › pdf › 1410

   cuDNN: Efficient Primitives for Deep Learning. Sharan Chetlur, Cliff Woolley, Philippe Vandermersch, Jonathan Cohen, John Tran. NVIDIA. Santa Clara, CA 95050. fschetlur, jwoolley, philippev, jocohen, johntrang@nvidia.com.

   • Autor: Sharan Chetlur, Cliff Woolley, Philippe Vandermersch, Jonathan Cohen, John Tran, Bryan Catanzaro, Ev...

   • Publish Year: 2014

7. research.nvidia.com › publication › 2014-12_cudnn-efficientcuDNN: Efficient Primitives for Deep Learning | Research - NVIDIA

   research.nvidia.com › publication › 2014-12_cudnn-efficient

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   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.

8. ar5iv.labs.arxiv.org › html › 1410[1410.0759] cuDNN: Efficient Primitives for Deep Learning - ar5iv

   ar5iv.labs.arxiv.org › html › 1410

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   3. März 2024 · Abstract. We present a library of efficient implementations of deep learning primitives. Deep learning workloads are computationally intensive, and optimizing their kernels is difficult and time-consuming. As parallel architectures evolve, kernels must be reoptimized, which makes maintaining codebases difficult over time.