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

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

    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 ...

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

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

    • 12
    • 25
    • NVIDIA
    • San Jose, California, United States

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

    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.

    • Sharan Chetlur, Cliff Woolley, Philippe Vandermersch, Jonathan Cohen, John Tran, Bryan Catanzaro, Ev...
    • 2014

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

    Evan Shelhamer. UC Berkeley Berkeley, CA 94720. shelhamer@eecs.berkeley.edu. Abstract. We present a library of efficient implementations of deep learning primitives. Deep learning workloads are computationally intensive, and optimizing their ker-nels is difficult and time-consuming.

    • Sharan Chetlur, Cliff Woolley, Philippe Vandermersch, Jonathan Cohen, John Tran, Bryan Catanzaro, Ev...
    • 2014

  6. developer.nvidia.com › gpugems › gpugems2Chapter 35. GPU Program Optimization | NVIDIA Developer

    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.

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

    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.