Phase-change materials for energy-efficient photonic memory and computing
Neuromorphic algorithms achieve remarkable performance milestones in tasks where humans have traditionally excelled. The breadth of data generated by these paradigms is, however, unsustainable by conventional computing chips. In-memory computing hardware aims to mimic biological neural networks and...
| Auteurs principaux: | , , , , , , , , |
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| Format: | Journal article |
| Langue: | English |
| Publié: |
Springer Nature
2022
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