DESIGN AND PERFORMANCE ANALYSIS OF AN IMPROVED LOW-POWER 8T SRAM CELL FOR ENHANCED WRITABILITY

Abstract

In modern electronics, memory is a core component that enables data storage and retrieval, but cache memory is even more critical due to its direct connection to the CPU. Cache memory is designed to provide the processor with quick access to frequently used data and instructions. It relies on millions of SRAM cells, which must be highly efficient to maintain performance. These cells are required to operate with low power both static and dynamic while ensuring data remains stable and accessible. Fast read response times are also essential so that the processor is not bottlenecked during execution. This review discusses the core elements of SRAM cell design and how they impact performance. It starts by explaining why SRAM matters in computing systems and how each cell functions. The focus is placed on data stability, speed during read and write operations, and minimizing power consumption. The review explores different cell architectures and the trade-offs they involve. It addresses key design challenges, including sensitivity to noise and issues caused by manufacturing variations. It also covers improvements such as assist techniques and feedback loops. The impact of shrinking technology nodes on these cells is reviewed in detail. The performance of SRAM cells is evaluated by analyzing factors like read and write delay, write margin, stability, and power usage. This review explores how variations in design elements such as transistor sizes, supply voltage, and output loading affect these characteristics. It also looks into how process fluctuations impact the reliability and yield of SRAM cells and outlines possible solutions to enhance long-term performance and stability. This work presents a detailed Monte Carlo analysis of various 7T and 8T SRAM cell topologies at the 45nm technology node, simulated using the Cadence Virtuoso tool. The primary focus is to evaluate and compare the static and dynamic characteristics of these designs against a newly proposed 8-transistor SRAM cell, named 8TSEDPP. The analysis encompasses critical design metrics such as Hold Static Noise Margin (HSNM), Read Static vi Noise Margin (RSNM), Write Margin (WM or N-Curve), dynamic power consumption, and access times for read and write operations. The proposed 8TSEDPP circuit stands out with significant improvements in stability, power efficiency, and performance balance. In terms of RSNM, the proposed cell achieves 205 mV, outperforming all other designs, including 7TDESPP and 7TSESPK, with an average improvement of over 45%. The Write Margin also shows a notable enhancement, reaching 510.41 mV, which represents a 13.5% increase over traditional 7T cells like 7TDESPC and 7TDESPL. Despite being a more complex circuit, the dynamic power consumption of the proposed 8TSEDPP is just 317.8 nW, which is a remarkable 67.6% reduction compared to the baseline 7TDESPT design. This makes the proposed cell highly suitable for low-power applications without sacrificing stability. Timing analysis further strengthens the case for 8TSEDPP. The Write ‘0’ access time is measured at 205 ps, while Write ‘1’ access time is 291.6 ps, both of which remain within acceptable limits for high-performance applications. Although some 7T cells exhibit slightly faster access times, they lag significantly in power and noise margin performance. The Read Access Time of 510.41 ps, although not the fastest, offers a balanced trade-off given the robustness in other areas. Overall, the 8TSEDPP SRAM cell demonstrates the best overall balance across all performance, stability, and power metrics, validating its suitability for energy-sensitive and high- reliability memory applications. The proposed design is particularly promising for next-generation VLSI circuits used in portable, embedded, and IoT-based devices, where low leakage, reliable write operations, and immunity to process variations are critical. The results obtained through extensive simulations confirm that 8TSEDPP is a strong candidate for replacing or complementing traditional SRAM architectures in future semiconductor designs.