Abstract
A novel Resistive random access memory (ReRAM)-based Compute-in-memory (CIM) macro is proposed to overcome the limited accuracy and throughput of a conventional ReRAM-based CIM macro that results from to the low R-Ratio and large variation of ReRAM. The proposed structure consists of 1T2R1C bit-cells and 4-kb ReRAM-based nvCIM architecture with ternary weight and ternary input. Ternary multiplication is implemented with voltage division between paired ReRAM devices within a bit-cell to make the output voltage variation tolerant and less sensitive to low R-ratios. An accumulation operation is realized with capacitive coupling so that linearity can be guaranteed for a large number of operands, allowing accurate and fast multiply-and-accumulate (MAC) operations. For comprehensive validation of the proposed CIM macro, the Verilog-A models for ReRAM devices with an adjustable R-ratio and adjustable variations are adopted to perform simulation on various R-ratio and variation conditions. With the peripheral circuits designed in 180-nm CMOS technology, the proposed CIM macro is confirmed to have high variation tolerance, high throughput, and less sensitivity to a low R-ratio, resulting in a high ternary DNN accuracy of 99.07% (0.01% drop) for the MNIST and 83.79% (0.38% drop) for the CIFAR-10 data sets with an R-ratio as low as 38 and 20%/40% low/high resistance variation.
| Original language | English |
|---|---|
| Pages (from-to) | 2845-2856 |
| Number of pages | 12 |
| Journal | IEEE Transactions on Circuits and Systems I: Regular Papers |
| Volume | 69 |
| Issue number | 7 |
| DOIs | |
| State | Published - 1 Jul 2022 |
| Externally published | Yes |
Keywords
- capacitive-coupling
- Computing-in-memory (CIM)
- deep neural network (DNN)
- nonvolatile memory (NVM)
- resistive RAM (ReRAM)
- voltage division
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