Horovod (machine learning)
 | |
| Developer(s) | Uber |
|---|---|
| Initial release | August 9, 2017[1] |
| Stable release | v0.28.1[2]
/ June 12, 2023 |
| Written in | Python, C++, CUDA |
| Platform | Linux, macOS, Windows |
| Type | Artificial intelligence ecosystem |
| License | Apache License 2.0 |
| Website | 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]
See also
[edit]References
[edit]- ^ Alex Sergeev (August 9, 2017). "Release v0.9.0 · horovod/horovod". horovod. Retrieved July 9, 2020.
Initial release
- ^ "Releases · horovod/horovod". horovod. Retrieved July 11, 2023.
- ^ Khari Johnson (December 13, 2018). "Uber brings Horovod project for distributed deep learning to Linux Foundation". VentureBeat. Retrieved July 9, 2020.
- ^ "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.
External links
[edit]| Open source | |
|---|---|
| Proprietary |
|
Differentiable computing | |
|---|---|
| General | |
| Hardware | |
| Software libraries | |
| |
 | This artificial intelligence-related article is a stub. You can help Wikipedia by expanding it. |