Balancing Specialized Versus Flexible Computation in Brain–Computer Interfaces
Balancing Specialized Versus Flexible Computation in Brain–Computer Interfaces
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平衡脑机接口中的专业计算与灵活计算
DOI：
10.1109/mm.2021.3065455
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发表时间：
2021-05
期刊：
影响因子：
3.6
通讯作者：
I. Karageorgos;Karthik Sriram;J. Veselý;Nick Lindsay;Xiayuan Wen;Michael Wu;M. Powell;D. Borton;R. Manohar;A. Bhattacharjee
中科院分区：
文献类型：
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作者：
I. Karageorgos;Karthik Sriram;J. Veselý;Nick Lindsay;Xiayuan Wen;Michael Wu;M. Powell;D. Borton;R. Manohar;A. Bhattacharjee
我们正在构建HALO，这是一种灵活的超低功耗处理架构，用于植入式脑机接口（BCI），可直接与生物神经元进行真实的实时通信。本文讨论了BCI设计人员必须平衡的刚性功耗、性能和灵活性权衡，以及我们如何通过HALO的特定领域硬件加速器、通用微控制器和可配置互连来克服这些权衡。我们的评估使用从非人类灵长类动物体内收集的神经元数据，沿着全栈算法芯片协同设计，表明HALO实现了灵活性和上级性能比现有的植入式BCI。
We are building HALO, a flexible ultralow-power processing architecture for implantable brain– computer interfaces (BCIs) that directly communicate with biological neurons in real time. This article discusses the rigid power, performance, and flexibility tradeoffs that BCI designers must balance, and how we overcome them via HALO’s palette of domain-specific hardware accelerators, general-purpose microcontroller, and configurable interconnect. Our evaluations using neuronal data collected in vivo from a nonhuman primate, along with full-stack algorithm to chip codesign, show that HALO achieves flexibility and superior performance per watt versus existing implantable BCIs.