horovod logo

horovod

archived
horovod/horovod

Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

GraphCanon updated Sep 26, 2026 · GitHub synced Sep 26, 2026

69views this month

15k stars2.2k forksLast push Sep 17, 2026 Python Other

Decision brief

Simplify distributed deep learning training for TensorFlow, Keras, PyTorch, and MXNet with minimal code changes.

Good fit when

  • When you need to scale your training across multiple GPUs or nodes with little modification to existing scripts.
  • For environments where simplicity and quick setup of multi-GPU training are prioritized.

Avoid when

  • Avoid when extensive customization beyond core training is needed, as Horovod simplifies processes which might limit flexibility.
  • Not recommended if your project relies heavily on specific features not well-supported in Horovod's integration with frameworks like TensorFlow or PyTorch.

Observed Jul 12, 2026 · Source: enrich:decision_facts

Verify the decision

Maintenance and security

Full trust report
Maintenance
Archived (8d since push)
As of Sep 26, 2026
Provenance
Not a fork · Organization account
As of Sep 26, 2026
Security (OSV)
No lockfile
As of Jul 11, 2026

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

pip install horovod
PyPI

Similar tools

Same-category neighbours. No typed graph edges are catalogued for this tool yet.

Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

Horovod is a distributed deep learning training framework designed to make distributed deep learning fast and easy to use. It supports popular machine learning frameworks like TensorFlow, Keras, PyTorch, and Apache MXNet, facilitating multi-GPU and multi-node scaling.

Capability facts

Languages
python

Source: github.language · Sep 26, 2026

Categories

Tags

README

.. raw:: html <p Due to inactivity, this project was archived in September 2026. The contents will remain available for historical purposes.</p <p align="center" <img src="https://user images.githubusercontent.com/16640218/34506318 84d0c06c efe0 11e7 8831 0425772ed8f2.png" alt="L...

For agents

This page has a .md twin and JSON over the API.

Was this helpful?

Anonymous feedback helps us improve pages and translations.