NVIDIA and Solidigm Rewrite Storage Rules for AI's KV Cache
shashib · x · 2026-08-02
NVIDIA and Solidigm are co-designing solid-state drives that sit directly inside the GPU memory hierarchy to handle the growing KV cache in LLMs.
The core premise is that with high bandwidth memory (HBM) costing around $10,000 per terabyte, pushing overflow context to flash storage is cheaper. This new architecture allows the storage to drop data bytes because, in this specific scenario, a dropped byte simply triggers a recompute rather than a catastrophic data loss event.
More from Infra
- Baidu open-sources FlashMask: up to 1.55x faster than FlashAttention-4 for long-context training — BaiduResearch · 2026-10-16
- GYRO quant of Qwen3.8-Flash-Next tested: near Q3 quality at much smaller size — PlasticRevenue4601 · 2026-10-16
- RL train-sample systems are frontier AI's hardest infra problem — and a trade secret — brianryhuang · 2026-10-16
- Local tuning of GLM-5.3-Flash on 2×GB10 lifts decode from 49 to 58 tok/s — EAccelerate_42 · 2026-10-16
- 3x DGX Spark cluster runs GLM-5.3-Flash locally behind a proxy, 1.75M tokens/day at 119W — Teknium · 2026-10-16
- Optuna creator Akiba: when 2 hyperparameters cost $20M, what's left for BO/HPO — Stefania_druga · 2026-10-16