20180613 [TensorFlow分散学習] Horovodによる分散学習の実装方法と解説
2018年6月13日に実施した勉強会の講演資料です。 [TensorFlow分散学習]Horovodによる分散学習の実装方法と解説 発表者：LeapMind Inc. Hideaki Masuda
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GitHub - horovod/horovod: Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
The primary motivation for this project is to make it easy to take a single-GPU training script and successfully scale it to train across many GPUs in parallel. This has two aspects: How much modification does one have to make to a program to make it distributed, and how easy is it to run it? How much faster would it run in distributed mode? Internally at Uber we found the MPI model to be much mor
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tutorial/imagenet/12min-imagenet-training.MD · master · Yin, Junqi / mldl-hpc · GitLab
Add in-place broadcast for TensorFlow by maxhgerlach · Pull Request #3128 · horovod/horovod
Scalable deep learning training using multi-node parallel jobs with AWS Batch and Amazon FSx for Lustre | Amazon Web Services
Hyperas + Horovod Example · GitHub
horovod/running.md at master · horovod/horovod · GitHub
