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

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 50× higher retention time compared to the state-of-the-art designs.