Single ended computational SRAM bit-cell

Dual port SRAM plays an important role in maintaining the bandwidth of dataflow between memory and processor. To improve data stability and bandwidth, the memory industry moved from conventional 6 transistor (6T) to 8 transistor (8T) SRAM but compromised on the layout area for additional stability. To address the trade-off between area and reliability, a novel Single Ended 8T SRAM is proposed in this paper along with its static analysis, transient response and power consumption, to observe its efficiency and reliability. The proposed SRAM bit-cell architecture is also capable of in-memory computation, thereby potentially avoiding the Von-Neumann bottleneck problem for some computations. In particular, the proposed SRAM can perform in-memory NAND and NOR operations, and may be useful for low-power and high-performance machine learning and neural network hardware architectures.

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