Microprocessors use static random-access memory (SRAM) cells in the cache memory design. As a part of the central computing component, their performance is critical. Modern system-on-chips (SoC) escalate performance pressure because only 10–15% of the transistors accounts for logic, while the remaining transistors are for the cache memory. Moreover, modern implantable, portable and wearable electronic devices rely on artificial intelligence (AI), demanding an efficient and reliable SRAM design for compute-in-memory (CIM). For performance benchmark achievements, maintaining reliability is a major concern in recent technological nodes. Specifically, battery-operated applications utilize low-supply voltages, putting the SRAM cell’s stability at risk. In modern devices, the off-state current of a transistor is becoming comparable to the on-state current. On the other hand, process variations change the transistor design parameters and eventually compromise design integrity. Furthermore, sensitive information processing, environmental conditions and charge emission from IC packaging materials undermine the SRAM cell’s reliability. FinFET-SRAMs, with aggressive scaling, have taken operation to the limit, where a minute anomaly can cause failure. This article comprehensively reviews prominent challenges to the SRAM cell design after classifying them into five distinct categories. Each category explains underlying mathematical relations followed by viable solutions.

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