TSMC 22nm近阈值工作频率提升效果测试数据

本数据集是基于TSMC 22nm工艺节点构建的高能效AI处理器宽电压（0.6VDD~1.2VDD）的实测数据，旨在为解决宽电压设计中的能效优化与时序收敛挑战提供近阈值频率性能的实测参考。数据集的核心内容涵盖了两大关键弹性设计技术的测试数据：一是自适应电压调节（AVS）数据，记录了在不同基准频率下闭环搜索得到的系统最低工作电压与能耗极值；二是自适应频率调节（AFS）数据，记录了在0.6VDD近阈值区利用动态时序裕量所能达到的最高物理工作频率。在质量控制方面，本研究采用了经过严格校准的高精度硬件设施，并通过第三方全流程现场监督与认证机制，确保了数据的真实性与准确性。作为标准化的硅后实测结果，本数据集面对芯片的能效潜力与性能边界研究，为校准设计裕量、修正低电压时序分析（STA）模型及优化电源管理策略提供了可靠的物理实证数据支持。该数据集已作为重点研发计划项目成果的重要组成部分，进行规范化汇交与管理。

This dataset contains measured data for high-efficiency AI processors fabricated using the TSMC 22nm process node, with a tested wide voltage range of 0.6VDD to 1.2VDD. It is intended to provide measured reference data for near-threshold frequency performance to address the challenges of energy efficiency optimization and timing closure in wide-voltage design workflows. The core of the dataset covers test data from two critical resilient design technologies: first, Adaptive Voltage Scaling (AVS) data, which records the minimum operating voltage and extreme energy consumption of the system derived through closed-loop searches under various reference frequencies; second, Adaptive Frequency Scaling (AFS) data, which records the maximum physical operating frequency attainable by leveraging dynamic timing margins in the 0.6VDD near-threshold region. For quality assurance, this study utilized strictly calibrated high-precision hardware facilities, and ensured the authenticity and accuracy of the dataset via third-party full-process on-site supervision and certification mechanisms. As standardized post-silicon measured results, this dataset offers reliable physical empirical data support for calibrating design margins, revising low-voltage Static Timing Analysis (STA) models, and optimizing power management strategies, targeting research on chip energy efficiency potential and performance boundaries. This dataset has been formally submitted and managed as an important component of the achievements of key research and development plan projects.

搜集汇总

背景与挑战

背景概述

该数据集基于TSMC 22nm工艺节点，提供了高能效AI处理器在宽电压范围内的实测数据，核心包括自适应电压调节（AVS）和自适应频率调节（AFS）两大技术的测试结果，如最低工作电压和近阈值区最高频率。通过严格校准和第三方监督确保数据准确性，旨在为芯片能效优化、时序收敛挑战及电源管理策略提供物理实证支持。