OptiReduce
OptiReduce is a resilient and tail-optimal collective-communication framework for distributed deep learning in the cloud. It seamlessly integrates with PyTorch's Distributed Data Parallel (DDP) training to optimize communication performance in high-tail latency environments.
Why OptiReduce?
🚀 Faster Training
- Eliminates bottlenecks from stragglers and slow workers
- Optimizes performance in high-tail latency environments
- Reduces training time, cost, and resource usage
💡 Key Features
- Bounded-Loss Reliability: Speeds up training by tolerating small controlled loss
- Tail Latency Optimization: Efficiently handles network variability
- PyTorch Integration: Seamless integration with PyTorch DDP
🔧 Technical Highlights
- Compatible with Mellanox ConnectX NICs
- Efficient memory pool management
- Zero-copy operations for maximum performance
Choose your path with OptiReduce
👉 Quick Start
📚 Learn More
Research
OptiReduce was presented at NSDI '25. Read our paper:
📄 OptiReduce: Resilient and Tail-Optimal AllReduce for Distributed Deep Learning in the Cloud
Support
Need help? Here are your options:
- Review all the documentation
- Open an issue
- Review installation guide for setup help