AVATAR: an aging- and variation-aware dynamic timing analyzer for application-based DVAFS
Zuodong Zhang, Zizheng Guo, Yibo Lin, Runsheng Wang, Ru Huang
Abstract
As the timing guardband continues to increase with the continuous technology scaling, better-than-worst-case (BTWC) design has gained more and more attention. BTWC design can improve energy efficiency and/or performance by relaxing the conservative static timing constraints and exploiting the dynamic timing margin. However, to avoid potential reliability hazards, the existing dynamic timing analysis (DTA) tools have to add extra aging and variation guardbands, which are estimated under the worst-case corners of aging and variation. Such guardbanding method introduces unnecessary margin in timing analysis, thus reducing the performance and efficiency gains of BTWC designs. Therefore, in this paper, we propose AVATAR, an aging- and variation-aware dynamic timing analyzer that can perform DTA with the impact of transistor aging and random process variation. We also propose an application-based dynamic-voltage-accuracy-frequency-scaling (DVAFS) design flow based on AVATAR, which can improve energy efficiency by exploiting both dynamic timing slack (DTS) and the intrinsic error tolerance of the application. The results show that a 45.8% performance improvement and 68% power savings can be achieved by exploiting the intrinsic error tolerance. Compared with the conventional flow based on the corner-based DTA, the additional performance improvement of the proposed flow can be up to 14% or the additional power-saving can be up to 20%.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext d8af7f7f-13de-4796-a15b-3becce022b5dRelated papers
- A Cross-Layer Power and Timing Evaluation Method for Wide Voltage ScalingWenjie Fu, Leilei Jin, Ming Ling, Yu Zheng et al.DAC 2020 · 5 citations
- Reducing DRAM Latency via In-situ Temperature- and Process-Variation-Aware Timing Detection and AdaptionYuxuan Qin, Chuxiong Lin, Mingche Lai, Zhang Luo et al.DAC 2024 · 1 citation
- TEVoT: Timing Error Modeling of Functional Units under Dynamic Voltage and Temperature VariationsXun Jiao, Dongning Ma, Wanli Chang, Yu JiangDAC 2020 · 11 citations
- PVTSizing: A TuRBO-RL-Based Batch-Sampling Optimization Framework for PVT-Robust Analog Circuit SynthesisZichen Kong, Xiyuan Tang, Wei Shi, Yiheng Du et al.DAC 2024 · 17 citations
- Watwaos: A Framework for Worst-Case-Aware Tailoring and Whole-System Analysis of Energy-Constrained Real-Time SystemsTobias Häberlein, Eva Dengler, Phillip Raffeck, Peter WägemannRTSS 2025
