Distributed Brain-Computer Interfacing With a Networked Multiaccelerator Architecture

被引：0
|
作者：
Pothukuchi, Raghavendra Pradyumna [1 ]
Sriram, Karthik [1 ]
Gerasimiuk, Michal [1 ]
Ugur, Muhammed [2 ]
Manohar, Rajit [2 ,3 ]
Khandelwal, Anurag [2 ]
Bhattacharjee, Abhishek [2 ]
机构：
[1] Yale Univ, New Haven, CT 06511 USA
[2] Yale Univ, Comp Sci, New Haven, CT 06511 USA
[3] Yale Univ, Elect Engn, New Haven, CT 06511 USA
来源：
IEEE MICRO | 2024年 / 44卷 / 04期
基金：
美国国家科学基金会;
关键词：
Electrodes; Implants; Program processors; Sorting; Computer architecture; Decoding; Brain-computer interfaces;
D O I：
10.1109/MM.2024.3411881
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
SCALO is the first distributed brain-computer interface (BCI) consisting of multiple wireless-networked implants placed on different brain regions. SCALO unlocks new treatment options for debilitating neurological disorders and new research into brainwide network behavior. Achieving the fast and low-power communication necessary for real-time processing has historically restricted BCIs to single brain sites. SCALO also adheres to tight power constraints but enables fast distributed processing. Central to SCALO's efficiency is its realization as a full stack distributed system of brain implants with accelerator-rich compute. SCALO balances modular system layering with aggressive cross-layer hardware-software co-design to integrate compute, networking, and storage. The result is a lesson in designing energy-efficient networked distributed systems with hardware accelerators from the ground up.
引用
收藏
页码：106 / 115
页数：10
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