HALO: A Flexible and Low Power Processing Fabric for Brain-Computer Interfaces

Bhattacharjee, Abhishek; Manohar, Rajit

doi:10.1109/hcs55958.2022.9895612

Cited by 1 publication

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A key takeaway from Sections II-B and II-C is the need for flexible support of compute on emerging BCIs. Indeed, this is a topic explored in recent work on the HALO architecture for BCIs [23,69,70]. Prior to HALO, power efficiency was achieved by specializing BCIs to offer a specific type of computation for a specific brain region.…”

Section: Flexibility As a Goal In Brain-computer Interface Designmentioning

confidence: 99%

A Multi-Site Accelerator-Rich Processing Fabric for Scalable Brain-Computer Interfacing

Sriram¹,

Pothukuchi²,

Michał³

et al. 2023

Preprint

View full text Add to dashboard Cite

Hull 1 is an accelerator-rich distributed implantable brain-computer interface (BCI) that reads biological neurons at data rates that are 2-3 orders of magnitude higher than the prior art, while supporting many neuroscientific applications. Prior approaches have restricted brain interfacing to tens of megabits per second in order to meet two constraints necessary for effective operation and safe long-term implantation-power dissipation under tens of milliwatts and response latencies in the tens of milliseconds. Hull also adheres to these constraints, but is able to interface with the brain at much higher data rates, thereby enabling, for the first time, BCI-driven research on and clinical treatment of brain-wide behaviors and diseases that require reading and stimulating many brain locations. Central to Hull's power efficiency is its realization as a distributed system of BCI nodes with accelerator-rich compute. Hull 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 networked distributed systems with hardware accelerators from the ground up.

show abstract

Section: Flexibility As a Goal In Brain-computer Interface Designmentioning

confidence: 99%