A new research paper from BitRipple, in collaboration with UC Berkeley, Intel, and CoreWeave, demonstrates how our LT3™ transport technology unlocks major efficiency gains in large-scale AI training.
Traditional network protocols leave GPUs idle due to retransmissions, congestion, and path collisions - wasting precious compute time. Our simulations show that LT3™ eliminates these bottlenecks by combining erasure-coded packet spraying with GPU-resident decoding.
🔹 30–40% reduction in Collective Completion Time (CCT)
🔹 5–10% improvement in Effective Training Time Ratio (ETTR)
🔹 Performance approaching the theoretical physics limit of GPU clusters
The best part? LT3™ achieves these gains with no hardware or fabric changes - just a drop-in software upgrade.
Contact Us, and we will send you the full paper to explore the design, results, and deployment roadmap.