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

页码：1006 / 1025

页数：20

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