Shadow Void Optimization of Microelectronic Packages with Tree-Based Learners
29th IEEE Workshop on Signal and Power Integrity, SPI 2025, Gaeta, İtalya, 11 - 14 Mayıs 2025, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Doi Numarası: 10.1109/spi64682.2025.11014381
- Basıldığı Şehir: Gaeta
- Basıldığı Ülke: İtalya
- Anahtar Kelimeler: shadow voiding, optimization, sequential sampling, decision tree
- Boğaziçi Üniversitesi Adresli: Evet
Özet
Shadow voiding is a critical technique for optimizing second-level interconnect (SLI) designs in microelectronic packages, aiming to minimize impedance mismatches while adhering to manufacturing and electrical constraints. This paper introduces a tree-based active learning algorithm for shadow void optimization. The proposed method efficiently explores geometric design parameters using decision trees and truncated SVD to reduce dimensionality. High-performing designs are identified via penalized regression within partitioned subspaces and evaluated through sequential sampling. The algorithm is applied to a 7-2-7 package, demonstrating significant improvements in electrical performance and computational efficiency. Results show that tree-based learners effectively characterize the design space, making them a practical solution for high-dimensional optimization problems in microelectronics.