Since the invention of the transistor in 1947, computing development has seen a consistent doubling of the number of transistors that can fit on a chip. But that trend, known as Moore's Law, may reach its limit as components of submolecular size encounter problems with thermal noise, making further scaling impossible.
In their paper published this week in Applied Physics Reviews, from AIP Publishing, authors Jack Kendall, of Rain Neuromorphics, and Suhas Kumar, of Hewlett Packard Labs, present a thorough examination of the computing landscape, focusing on the operational functions needed to advance brain-inspired neuromorphic computing. Their proposed pathway includes hybrid architectures composed of digital architectures, alongside a resurgence of analog architectures, made possible by memristors, which are resistors with memory that can process information directly where it is stored.
"The future of computing will not be about cramming more components on a chip but in rethinking processor architecture from the ground up to emulate how a brain efficiently processes information," Kumar said.
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