DisTrO: Revolutionizing Distributed Training

Distributed Training Optimization (DisTrO) is a groundbreaking protocol that addresses one of the most significant bottlenecks in large-scale AI training: communication overhead between nodes.

The Communication Problem

Traditional distributed training requires constant synchronization of gradients between nodes, consuming enormous bandwidth and limiting scalability. DisTrO fundamentally reimagines this process.

How DisTrO Works

Through decoupled momentum optimization and intelligent gradient compression, DisTrO achieves communication reduction of 1000x to 10000x while maintaining model quality and convergence guarantees.