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Tutorials and scripts to use Summit in order to scale up your Python deep learning projects. It covers basics of data parallelism and goes over what to add in your code to parallelize your training process.
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distributed deep learning examples on Summit for Keras, PyTorch, and TensorFlow.
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Domain decomposition with automatic halo exchange using pytorch multigpu as well as the new RPC interface in pytorch 1.4.
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Code to reproduce the results found in "Simulating the Shastry-Sutherland Ising Model using Quantum Annealing." Manuscript can be found at https://arxiv.org/abs/2003.01019.
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Kelleher, Michael / Python for Computational Earth Sciences
BSD 3-Clause "New" or "Revised" LicenseShort course for the Computational Earth Sciences group on Python tools and best practices.
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sans-ldrd / model-generator-sans
Apache License 2.0Updated -
Tutorials and scripts to use Summit in order to scale up your Python deep learning projects. It covers basics of data parallelism and goes over what to add in your code to parallelize your training process.
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distributed deep learning examples on Summit for Keras, PyTorch, and TensorFlow.
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Set up a BlazingSQL container in Google cloud Kubernetes Engine (GKE)
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distributed deep learning examples on Summit for Keras, PyTorch, and TensorFlow.
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