mlsanityData to 7 Oct 2026

MAVIREC: ML-Aided Vectored IR-DropEstimation and Classification

arXiv 2012.10597 ↗First posted 19 Dec 2020cs.ARcited by 10

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Abstract (arXiv)

Vectored IR drop analysis is a critical step in chip signoff that checks the power integrity of an on-chip power delivery network. Due to the prohibitive runtimes of dynamic IR drop analysis, the large number of test patterns must be whittled down to a small subset of worst-case IR vectors. Unlike the traditional slow heuristic method that select a few vectors with incomplete coverage, MAVIREC uses machine learning techniques -- 3D convolutions and regression-like layers -- for accurately recommending a larger subset of test patterns that exercise worst-case scenarios. In under 30 minutes, MAVIREC profiles 100K-cycle vectors and provides better coverage than a state-of-the-art industrial flow. Further, MAVIREC's IR drop predictor shows 10x speedup with under 4mV RMSE relative to an industrial flow.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Dec 2020.

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Citing papers per year: 2021: 1; 2022: 1; 2023: 0; 2024: 3; 2025: 3; 2026: 2.

10 papers.