Ladder-residual architecture enables efficient parallelism in large language model inference by overlapping computation with communication between GPUs.

• Reduces inference time by intelligently parallelizing operations across multiple GPUs
• Minimizes the impact of communication bottlenecks that typically limit distributed processing
• Scales more effectively as the number of devices increases compared to traditional approaches
• Demonstrates practical performance improvements for real-world LLM deployment

This engineering innovation addresses a critical challenge in deploying large language models at scale, enabling faster inference without sacrificing model quality, and improving resource utilization in multi-GPU environments.

Ladder-residual: parallelism-aware architecture for accelerating large model inference with communication overlapping