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English(EN) Ditching external DRAM cuts AI edge inference to 58.5ms and slashes boot time to 65.7ms. Tohoku University and automotive tier-one Aisin achieved this by embedd

东北大学和爱信嵌入STT-MRAM以加速AI边缘推理

东北大学的研究人员与汽车供应商爱信合作,通过将32MB的STT-MRAM直接嵌入到16nm的台积电芯片上,开发出一种新的AI边缘推理方法。这种集成消除了对外部DRAM的需求,从而将推理时间显著缩短至58.5毫秒,启动时间缩短至65.7毫秒。该创新还拥有50.7mJ/frame的能效,展示了非易失性存储器在先进驾驶辅助系统(ADAS)方面的量产就绪性。 AI

影响 这一发展可能导致更高效、更快速的边缘AI处理,从而影响自动驾驶汽车等设备的性能和能力。

排序理由 详细介绍AI硬件新技术的学术论文。[lever_c_demoted from research: ic=1 ai=0.7]

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东北大学和爱信嵌入STT-MRAM以加速AI边缘推理

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14 / 100
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详细介绍AI硬件新技术的学术论文。[lever_c_demoted from research: ic=1 ai=0.7]
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infra, product
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报道来源 [1]

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

    Ditching external DRAM cuts AI edge inference to 58.5ms and slashes boot time to 65.7ms. Tohoku University and automotive tier-one Aisin achieved this by embedd

    Ditching external DRAM cuts AI edge inference to 58.5ms and slashes boot time to 65.7ms. Tohoku University and automotive tier-one Aisin achieved this by embedding 32MB of STT-MRAM onto a 16nm TSMC chip, delivering 50.7mJ/frame efficiency. It's solid proof that non-volatile memor…