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English(EN) SK hynix is trying to bypass GPU memory limits by turning 3D NAND into active processors. Their new FeNAND research enables analog compute-in-memory directly in

SK海力士将3D NAND转变为AI处理器以绕过GPU内存限制

作者 PulseAugur 编辑部 · [1 个来源] ·

SK海力士正在开发FeNAND技术，该技术将处理能力直接集成到3D NAND闪存中。这项创新旨在通过实现内存中模拟计算来克服当前GPU内存的限制，从而使AI模型计算能够在其数据所在的位置进行。目标是降低AI推理的成本并提高效率。 AI

影响 这一发展可以通过减少对传统GPU内存的依赖，显著改变AI推理的经济性。

排序理由 该项目描述了用于AI推理的新型计算技术的研究。[lever_c_demoted from research: ic=1 ai=0.7]

在 Mastodon — mastodon.social 阅读 →

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SK海力士将3D NAND转变为AI处理器以绕过GPU内存限制

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该项目描述了用于AI推理的新型计算技术的研究。[lever_c_demoted from research: ic=1 ai=0.7]
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报道来源 [1]

  1. Mastodon — mastodon.social TIER_1 English(EN) · asiaai ·

    SK hynix 试图将 3D NAND 转化为有源处理器，以绕过 GPU 内存限制。其新的 FeNAND 研究可在其中直接实现模拟内存计算

    SK hynix is trying to bypass GPU memory limits by turning 3D NAND into active processors. Their new FeNAND research enables analog compute-in-memory directly inside flash storage. By executing parallel vector math where large language model weights actually live, South Korea is a…

    链接 asiaai.fyi/china-buys-million-nvidia-gpus…

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