  Hull 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 state of 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.
