Executive Summary

The Memory Crisis in LLM Inference—and How to Solve It

A distributed endpoint architecture that expands GPU memory capacity 6×, serves 16× more concurrent users, and reduces infrastructure costs by 36%.

Why This Matters: The Innovation Gap

No existing solution combines per-KV-head tracking, attention-aware eviction, RoPE-aware prefetch, and CXL controller intelligence. See the full competitive landscape →

Complete Visual Overview (14 Figures)

This comprehensive visual appendix covers the entire architecture from transformer fundamentals through final performance results.

Key Component Diagrams