SCALO: An Accelerator-Rich Distributed System for Scalable Brain-Computer Interfacing

被引：5
作者：
Sriram, Karthik [1 ,2 ]
Pothukuchi, Raghavendra Pradyumna [1 ]
Gerasimiuk, Michal [1 ]
Ugur, Muhammed [1 ]
Ye, Oliver [1 ]
Manohar, Rajit [1 ]
Khandelwal, Anurag [1 ]
Bhattacharjee, Abhishek [1 ]
机构：
[1] Yale Univ, New Haven, CT 06520 USA
[2] SCALO, Wroclaw, Poland
来源：
PROCEEDINGS OF THE 2023 THE 50TH ANNUAL INTERNATIONAL SYMPOSIUM ON COMPUTER ARCHITECTURE, ISCA 2023 | 2023年
关键词：
Brain-Computer Interfaces; BCI; HardwareAccelerators; Low Power; ACTION-POTENTIALS; SIGNAL; COMMUNICATION; OPTIMIZATION; STIMULATION; RECORDINGS; SEIZURES; PROGRESS; EPILEPSY; NEURONS;
D O I：
10.1145/3579371.3589107
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 brain-wide 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：1006 / 1025
页数：20
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