English(EN) SK hynix and TetraMem collaborate on experimental chip to bolster energy efficiency for edge AI devices — memristor-based in-memory SoC research leaves performance questions up in the air

SK hynix与TetraMem推出实验性节能AI边缘芯片

作者 PulseAugur 编辑部 · [1 个来源] · 2026-07-10 16:58

SK hynix与TetraMem合作开发了一款实验性芯片，旨在提高AI边缘设备的能效。该片上系统（SoC）采用了基于忆阻器的片上计算架构，特别优化了用于轻量级AI模型中常见的深度卷积运算的专用神经网络处理单元（NPU）。虽然该设计在降低功耗方面显示出潜力，但其理论峰值性能2.54 TOPS远未达到当前先进AI应用的要求。 AI

影响这款实验性芯片展示了一种用于边缘设备节能AI处理的新颖方法，尽管其当前的性能限制凸显了在平衡功耗与计算需求方面持续存在的挑战。

排序理由行业参与者和学术机构关于实验性芯片架构的研究论文。[lever_c_demoted from research: ic=1 ai=0.7]

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Tom's Hardware TIER_1 English(EN) · Anton Shilov · 2026-07-10 16:58

SK hynix and TetraMem collaborate on experimental chip to bolster energy efficiency for edge AI devices — memristor-based in-memory SoC research leaves performance questions up in the air

SK hynix, TetraMem, and the University of Southern California built a memristor-based in-memory computing system-on-chip for AI edge devices, achieving promising energy efficiency, but failed to demonstrate its full potential.

报道来源 [1]

SK hynix and TetraMem collaborate on experimental chip to bolster energy efficiency for edge AI devices — memristor-based in-memory SoC research leaves performance questions up in the air

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