研究目的
To propose a rapid and holistic technology evaluation methodology for exploratory design-technology co-optimization (DTCO) in beyond 7nm technologies, focusing on vertically stacked horizontal Nanosheets, to assess performance, power, and area scaling accurately.
研究成果
The proposed holistic evaluation methodology effectively links parasitic effects and realistic area scaling to performance-power metrics, demonstrating that MOL parasitic R&C significantly impact designs, and optimized M1 power staples can achieve substantial area reduction with minimal performance penalty, providing a valuable approach for early technology assessment in beyond 7nm nodes.
研究不足
The study focuses on horizontal Nanosheets and may not generalize to other device architectures; relies on simulation and early-stage technology assumptions, which may not capture all real-world manufacturing complexities; routing challenges in small track cells could limit applicability.
1：Experimental Design and Method Selection:
The methodology includes exploratory patterning fidelity assessment, performance-power evaluation, and realistic area scaling using block area assessment. It involves device TCAD for intrinsic characteristics, parasitic extraction linked to process assumptions, and timing-aware block area scaling to account for routing impacts.
2：Sample Selection and Data Sources:
Uses standard cells and SRAM designs, with key parameters for horizontal Nanosheet devices (e.g., width, MOL contacts) as specified in the paper.
3：List of Experimental Equipment and Materials:
Not explicitly detailed in the provided text; inferred use of simulation tools (e.g., Synopsys ICC2 for design and analysis).
4：Experimental Procedures and Operational Workflow:
Steps include optimizing Nanosheet width, assessing MOL parasitic resistance and capacitance variations, evaluating inverter designs (1X, 2X, 4X fingers), and analyzing block area scaling with M1 power staples.
5：Data Analysis Methods:
Performance metrics (e.g., frequency, Reff, Ceff) are normalized and compared; statistical analysis of parasitic effects and area scaling is performed using simulation data.
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