CORDIS Project
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BRAIN-CCC explores energy-efficient machine learning through neuromorphic computing using iontronic channels. The project aims to develop a prototype that allows direct training of machine learning models in hardware, significantly reducing energy consumption.
The energy consumption of machine learning (ML) is doubling every 2 months, outpacing global energy production within the next decade.
Neuromorphic computing, in particular, memristive crossbar arrays have shown energy reductions of 2 orders of magnitude in ML.
However, the training is typically performed on conventional computers, leading to significant energy losses.
Conical microfluidic channels have shown promise as volatile memristors, and there has been early progress toward achieving non…
UNIVERSITEIT UTRECHT
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South Korea, SEOUL
Type: University / higher education
Activity type: Higher or Secondary Education Establishments
SME: No
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