Suchergebnisse
Suchergebnisse:
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.
- 12
- 25
- NVIDIA
- San Jose, California, United States
Cliff Woolley, Sr. Manager, Developer Technology Software, NVIDIA. What limits the scalability of parallel applications? Efficiency of parallel computation tasks. Amount of exposed parallelism. Amount of work assigned to each processor. Expense of communications among tasks. Amount of communication.
- 1MB
- 56
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...
- arXiv:1410.0759 [cs.NE]
- 2014
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.
- California
- 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.
Sylvain Jeaugey, NVIDIA | Cliff Woolley, NVIDIA | Sreeram Potluri, NVIDIA | Ke Wen, NVIDIA | Nathan Luehr, NVIDIA GTC 2020 NCCL (NVIDIA Collective Communication Library) optimizes inter-GPU communication on PCI, NVIDIA NVLink, and Infiniband, powering large-scale training for most DL frameworks, including Tensorflow, PyTorch, MXNet, and Chainer.
