Horovod is an open-source distributed deep learning training framework designed to simplify multi-GPU and multi-node training. It leverages TensorFlow and PyTorch to enable efficient communication between workers, making it a popular choice for AI research and production.

Key Features

  • Cross-platform support: Works seamlessly with TensorFlow and PyTorch
  • 🚀 High-performance communication: Uses MPI for fast data exchange
  • 🛠️ Easy integration: Simplifies distributed training with minimal code changes
  • 🌐 Scalability: Supports training on clusters with hundreds of GPUs
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Use Cases

  • 🧠 Training large-scale models like Transformer or ResNet
  • 📈 Accelerating model optimization processes
  • 🧪 Enabling collaborative AI research across teams
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Getting Started

  1. 📦 Install Horovod via pip install horovod
  2. 🧾 Write a simple training script with distributed settings
  3. 🔄 Run on multi-GPU systems using horovodrun
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For deeper technical details, check our Horovod Tutorials section. 📘