SuanNi
SuanNi
Feb 27, 2026 · Artificial Intelligence

How Dual‑Channel Loading Doubles LLM Inference Throughput

The article analyzes the storage‑bandwidth bottleneck of agent‑style large language models, explains why traditional pre‑fill and decode architectures underutilize network resources, and details a dual‑channel loading and smart scheduling design that unlocks idle bandwidth, achieving up to 1.9× higher throughput in both offline and online inference workloads.

AI infrastructureDual-Channel LoadingKV-Cache
0 likes · 14 min read
How Dual‑Channel Loading Doubles LLM Inference Throughput
PaperAgent
PaperAgent
Feb 27, 2026 · Artificial Intelligence

How DualPath Eliminates Storage Bandwidth Bottlenecks in Agentic LLM Inference

This article analyzes the DualPath architecture that redesigns KV‑Cache data paths to overcome storage‑NIC saturation in Prefill‑Decode LLM systems, presenting theoretical proofs, detailed engineering solutions, and extensive offline and online benchmarks that demonstrate up to 2.25× performance gains.

DualPathLLM inferencePerformance optimization
0 likes · 9 min read
How DualPath Eliminates Storage Bandwidth Bottlenecks in Agentic LLM Inference