In-Memory Neural Network Accelerator based on eDRAM Cell with Enhanced Retention Time.

DAC(2023)

引用 1|浏览4
暂无评分
摘要
Logic compatible eDRAM cell-based computing-in-memory (CIM) neural network accelerators have been actively studied as an energy-efficient neural network computing platform thanks to their small cell size and low static power compared to SRAM. However, previous eDRAM-based CIM accelerators suffer from significant accuracy degradation caused by process, voltage, temperature (PVT) variations and short retention time. To overcome the issues, we introduce a PVT-variation tolerant capacitive coupling-based eDRAM cell that has a much longer retention time than previous works. Simulation results show that the proposed eDRAM cell has up to 50x higher retention time compared to the state-of-the-art designs.
更多
查看译文
关键词
cell size,eDRAM-based CIM accelerators,energy-efficient neural network computing platform,in-memory neural network accelerator,logic compatible eDRAM cell-based computing,PVT-variation tolerant capacitive coupling-based eDRAM cell,retention time enhancement
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要