A comparison of computing-in-memory with non-volatile memory types and SRAM in DNN training
In recent years, as Deep Neural Network (DNN) has been widely used in various artificial intelligence (AI) applications, the demands for energy efficiency and computational speed have continuously increased. Computing-in-Memory (CIM), as a potential solution, can significantly reduce the energy cons...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
AIP Publishing LLC
2025-03-01
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| Series: | AIP Advances |
| Online Access: | http://dx.doi.org/10.1063/9.0000891 |
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