Skip to content
Preprint

HBFSim: A Simulator for Exploring HBF in Memory Hierarchies for LLMs

Oct 2026 · 0 citations · 36 references
Computer Science

TL;DR

HBFSim is presented, an LLM-aware event-driven simulator for heterogeneous HBM+HBF memory systems that preserves application-level memory semantics while modeling flash-internal behavior and models HBM, HBF with host-managed flash translation, and conventional capacity tiers in one simulation driven by a calibrated serving frontend.

Abstract

High Bandwidth Flash (HBF) has recently emerged as a promising technology that provides terabyte-scale accelerator-local capacity at bandwidths approaching HBM, with a potential cost-per-bit advantage over HBM. However, its NAND foundation brings long latency, out-of-place updates, and finite write endurance directly into the accelerator memory hierarchy, making its effects on performance and lifetime difficult to predict. To study this emerging design space, we present HBFSim, an LLM-aware event-driven simulator for heterogeneous HBM+HBF memory systems that preserves application-level memory semantics while modeling flash-internal behavior. HBFSim models HBM, HBF with host-managed flash translation, and conventional capacity tiers in one simulation driven by a calibrated serving frontend. Using HBFSim, we study decoding of Llama-3.1-70B and Qwen3-235B-A22B under three workloads that differ in their input and output lengths. HBF serves data that does not fit in HBM 11.0--19.0$\times$ faster than host DRAM; HBM is better used to hold the running sequences'KV cache than as a cache for HBF; and at a published peak load of Llama-3.1-70B, HBF lasts 2.0 to 6.9 years, in proportion to the stacks that share the KV writes. The artifact is available at https://github.com/FlashLabAE/HBFSim and will track public HBF device data as it becomes available.

View source

Similar papers

Preprint Sep 2026

HBFSim: Fast and Faithful Simulation of High-Bandwidth Flash Under Real GPU Execution

High-Bandwidth Flash (HBF) places high-capacity NAND beside HBM to relieve the memory-capacity bottleneck of LLM inference, yet its system-level behavior cannot be evaluated before hardware becomes available. Cycle-level GPU simulators are too slow for production-scale models. Trace replay has a further shortcoming: it...

Yan-Peng Hu, Yi-Wei Yang, Yuan-Wu Zhu et al. · 0 citations
Preprint Sep 2026

HBF-Sim: An Extensible HBF Simulator for Large-scale GPU Memory Systems

High-bandwidth flash (HBF) is introduced to address the memory wall, which can co-package a dense NAND stack with the GPU, targeting the performance gap between near-accelerator bandwidth and flash density. HBF, however, is neither a large HBM nor a fast NVMe SSD. Its usable bandwidth depends on how GPU cache-line requ...

Ya-Qi Li, Jing Wang, Jun-Feng Wang et al. · 0 citations
#machine learning Preprint Sep 2026

Characterizing High Bandwidth Flash for LLM Serving

Large language model (LLM) serving requires substantial memory to store model weights and KV caches. As models grow larger and contexts become longer, memory capacity and bandwidth increasingly become bottlenecks for serving performance. Agentic workloads compound this pressure through repeated interactions over growin...

Zack Yu, Chloe Wong, C. Hooper et al. · 0 citations
#small language model Open access Jul 2026

Hot–Cold Tiering of HBM and High Bandwidth Flash for Agentic LLM Serving

This work places the hot set in HBM and the cold pool in HBF, forming a hot-cold KV hierarchy within the GPU memory tier, while flash-establishing HBF as a cold-tier complement to HBM rather than its replacement.

Jongjin Baek, Won Ji, Seungjae Yoo et al. · 0 citations
Book Open access Sep 2026

Beyond the HBM Wall: Coherent-Memory Oversubscription for AI Workloads on NVIDIA Grace Hopper

We realize an AI framework-agnostic interposer to test memory allocations on the NVIDIA Grace Hopper (GH200) Superchip, ranging from below the High Bandwidth Memory (HBM) limit, i.e., < 96 GB, to the HBM limit of 96 GB and beyond. When the HBM limit is exceeded, the coherent CPU+GPU memory of the GH200 can turn what wo...

Mohamed Abdelnaby, Wu-Chun Feng · 0 citations
Preprint Oct 2026

Lachesis: Lifetime-Aware KV Cache Placement for Agent Serving across HBM and High-Bandwidth Flash

Large language model (LLM) serving is increasingly dominated by agentic workloads, in which agents and their sub-agents accumulate context as KV cache across many requests, consuming substantial memory. High-bandwidth flash (HBF) is a promising solution, providing an order of magnitude greater capacity at HBM-class rea...

Jae-hun Yang, Jeong-Seok Lee, Haneul Park et al. · 1 citation

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.