A 129.83 TOPS/W Area Efficient Digital SOT/STT MRAM-Based Computing-In-Memory for Advanced Edge AI Chips
Author:
Affiliation:
1. Institute of Microelectronics,Agency for Science, Technology and Research,Singapore
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10181241/10181318/10181328.pdf?arnumber=10181328
Reference17 articles.
1. An Energy-Efficient Precision-Scalable ConvNet Processor in 40-nm CMOS
2. A 64 Kb Reconfigurable Full-Precision Digital ReRAM-Based Compute-In-Memory for Artificial Intelligence Applications
3. SOT-MRAM Based Analog in-Memory Computing for DNN Inference
4. UNPU: An Energy-Efficient Deep Neural Network Accelerator With Fully Variable Weight Bit Precision
5. 16. 4 An 89TOPS/W and 16. 3TOPS/mm2 all-digital SRAM-based full-precision compute-in memory macro in 22nm for machine-learning edge applications;chih;IEEE ISSCC Dig Tech Papers,2021
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2. Survey of Novel Architectures for Energy Efficient High-Performance Mobile Computing Platforms;Energies;2023-08-18
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