Synapses as a model: Solid-state memory in neuromorphic circuits

Certain tasks—such as recognizing patterns and language—are performed highly efficiently by a human brain, requiring only about one ten-thousandth of the energy of a conventional, so-called "von Neumann" computer. One of the reasons lies in the structural differences: In a von Neumann architecture, there is a clear separation between memory and processor, which requires constant moving of large amounts of data. This is time- and energy-consuming—the so-called von Neumann bottleneck. In the brain, the computational operation takes place directly in …

computer sciences memory neuromorphic solid state