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arXiv · 2608.13127

Potential Applications of HBF in LLM Serving Systems

Yihan Yin·Yinlun Zhao·Zhixin Yun·Guanying Wu·Feng Zhu·Kai Tao·Shu Li·Fei Huang·Zhe Zhang·Shuangchen Li·Hongzhong Zheng
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Abstract

LLM serving is increasingly constrained by memory capacity as model weights, KV caches, and the number of served model variants continue to grow. This report examines High-Bandwidth Flash (HBF) as a capacity-oriented extension to HBM-based serving systems. We first discuss how HBF can be integrated into the GPU memory hierarchy without undermining the bandwidth expected by the compute die. We then model the system-level value of added capacity as expanded residency for read-mostly model-state objects. Under this view, HBF can improve MoE serving by enabling more expert replicas and can improve multi-model serving by reducing model loading and supporting hot-model replication. Our simulation results show that these benefits depend on preserving the HBM-resident execution path while using HBF to expand the resident set of model weights.

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Yihan Yin, Yinlun Zhao, Zhixin Yun, Guanying Wu, Feng Zhu, Kai Tao, Shu Li, Fei Huang, Zhe Zhang, Shuangchen Li, Hongzhong Zheng. 2026-08-13. Potential Applications of HBF in LLM Serving Systems. https://arxiv.org/abs/2608.13127

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