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

被引：4

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

共 50 条

[41] Online EEG Classification of Covert Speech for Brain-Computer Interfacing
Sereshkeh, Alborz Rezazadeh
Trott, Robert
Bricout, Aurelien
Chau, Tom
INTERNATIONAL JOURNAL OF NEURAL SYSTEMS, 2017, 27 (08)
[42] Advanced Machine-Learning Methods for Brain-Computer Interfacing
Lv, Zhihan
Qiao, Liang
Wang, Qingjun
Piccialli, Francesco
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, 2021, 18 (05) : 1688 - 1698
[43] Classification Error Correction: A Case Study in Brain-Computer Interfacing
Poonawala, Hasan A.
Alshiekh, Mohammed
Niekum, Scott
Topcu, Ufuk
2017 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2017, : 3006 - 3012
[44] Effective Brain-Computer Interfacing Using BCI2000
Schalk, Gerwin
2009 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-20, 2009, : 5498 - 5501
[45] Asynchronous Brain-Computer Interfacing Based on Intended Movement Direction
Shimpo, Keita
Tanaka, Toshihisa
2013 35TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2013, : 4251 - 4254
[46] Brain-computer interfacing: science fiction has come true
Kuebler, Andrea
Holz, Elisa
Botrel, Loic
BRAIN, 2013, 136
[47] Knowledge Transfer for Reducing Calibration Time in Brain-Computer Interfacing
Dalhoumi, Sami
Dray, Gerard
Montmain, Jacky
2014 IEEE 26TH INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI), 2014, : 634 - 639
[48] Brain-Computer Interfacing for Bio-Perceptive and Rehabilitative Applications
Konar, Amit
Saha, Anuradha
Kar, Reshma
Chakraborty, Aruna
2015 THIRD INTERNATIONAL CONFERENCE ON COMPUTER, COMMUNICATION, CONTROL AND INFORMATION TECHNOLOGY (C3IT), 2015,
[49] Brain-computer interfacing: more than the sum of its parts
Scherer, Reinhold
Faller, Josef
Balderas, David
Friedrich, Elisabeth V. C.
Proell, Markus
Allison, Brendan
Mueller-Putz, Gernot
SOFT COMPUTING, 2013, 17 (02) : 317 - 331
[50] Did I Do That? Brain-Computer Interfacing and the Sense of Agency
Haselager, Pim
MINDS AND MACHINES, 2013, 23 (03) : 405 - 418

← 1 2 3 4 5 →