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Horovod (machine learning)

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This is an old revision of this page, as edited by Justin Ormont (talk | contribs) at 02:18, 10 July 2020 (removed Category:Google software and Category:Uber free software; corrected category date). The present address (URL) is a permanent link to this revision, which may differ significantly from the current revision.

Horovod
Developer(s)Uber
Initial releaseAugust 9, 2017; 6 years ago (2017-08-09)[1]
Stable release
v0.19.5[2] / May 6, 2020; 4 years ago (2020-05-06)
Repositorygithub.com/horovod/horovod/
Written inPython, C++, CUDA
PlatformLinux, macOS, Windows
TypeArtificial intelligence ecosystem
LicenseApache License 2.0
Websiteeng.uber.com/horovod/

Horovod is a free and open-source software framework for distributed deep learning training using TensorFlow, Keras, PyTorch, and Apache MXNet. Horovod is hosted under the Linux Foundation AI (LF AI).[3] Horovod has the goal of improving the speed, scale, and resource allocation when training a machine learning model[4]

Features

See also

References

  1. ^ Alex Sergeev (August 9, 2017). "Release v0.9.0 · horovod/horovod". horovod. Retrieved July 9, 2020. Initial release
  2. ^ "Releases · horovod/horovod". horovod. Retrieved July 9, 2020.
  3. ^ Khari Johnson (December 13, 2018). "Uber brings Horovod project for distributed deep learning to Linux Foundation". VentureBeat. Retrieved July 9, 2020.
  4. ^ "Projects - LF AI". Linux Foundation - LF AI. Retrieved July 9, 2020. Horovod, a distributed training framework for TensorFlow, Keras and PyTorch, improves speed, scale and resource allocation in machine learning training activities. Uber uses Horovod for self-driving vehicles, fraud detection, and trip forecasting. It is also being used by Alibaba, Amazon and NVIDIA.

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