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6 de may. de 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.
THE CHALLENGE OF COLLECTIVES. Collectives are central to scalability in a variety of key applications: • Deep Learning (All-reduce, broadcast, gather) • Parallel FFT (Transposition is all-to-all) • Molecular Dynamics (All-reduce) • Graph Analytics (All-to-all) • ….
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. Come discuss NCCL's performance, features, and latest advances.
1 de dic. de 2014 · Publication Date. Monday, December 1, 2014. Published in. Deep Learning and Representation Learning Workshop (NIPS2014) Research Area. Artificial Intelligence and Machine Learning. External Links. We present a library of efficient implementations of deep learning primitives.
3 de mar. de 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.
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. As parallel architectures evolve, kernels must be reoptimized, which makes maintaining codebases difficult over time.
