Horovod¶
Horovod is a framework for distributing training of Deep Learning models across multiple GPUs, which may be running on multiple machines
Logo |
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Website |
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Repository |
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Byline |
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. |
License |
Apache 2.0 |
Project age |
5 years 4 months |
Backers |
Linux Foundation AI & Data (Governed by), Uber (Creator) |
Lastest News (2022-10-13) |
v0.26.0 Better support for model parallel, more reduction operations for allreduce (min, max, product), grouped allgather and … more |
Size score (1 to 10, higher is better) |
6.0 |
Trend score (1 to 10, higher is better) |
4.75 |
Education Resources¶
URL |
Resource Type |
Description |
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https://horovod.readthedocs.io/en/stable/summary_include.html |
Documentation |
Official project documentation. |
Video |
This is a good tutorial video. |
Git Commit Statistics¶
Statistics computed using Git data through November 30, 2022.
Statistic |
Lifetime |
Last 12 Months |
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Commits |
53,867 |
1,763 |
Lines committed |
11,113,662 |
357,901 |
Unique committers |
183 |
37 |
Core committers |
17 |
8 |
Similar Projects¶
Project |
Size Score |
Trend Score |
Byline |
|---|---|---|---|
4.25 |
1.75 |
Distributed Tensorflow, Keras and PyTorch on Apache Spark/Flink & Ray |
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9.0 |
8.75 |
An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library. |