PiSPICE: Accelerating Post-Layout SPICE Simulation via Essential Parasitic Identification

As process nodes scale to more advanced technologies, post-layout simulations for integrated circuits have become increasingly complex, involving billions to trillions of nodes. The growing design complexity and transistor integration require more accurate and efficient post-layout SPICE simulations. However, existing methods for solving large-scale post-layout circuits face significant challenges due to high computational costs. In this paper, we propose a new approach, PiSPICE, which utilizes adjoint sensitivity analysis to identify critical parasitics and eliminate non-critical ones, effectively reducing the simulation scale and improving speed. By modeling parasitics and performing sensitivity analysis on pre-layout circuits, we significantly reduce the computational burden and avoid the overhead of directly analyzing sensitivities in large-scale postlayout circuits. By retaining only the critical parasitics and applying model order reduction to minimize their impact, while eliminating non-critical parasitics, PiSPICE achieves a speedup of up to 17.27 x in simulation with an error margin of less than 0.78% compared to the commercial simulator Spectre.

Authors

Institutions

Publication Details

Published
2025-06-22
DOI
https://doi.org/10.1109/dac63849.2025.11133011
Primary Topic
Semiconductor materials and devices
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

PiSPICE: Accelerating Post-Layout SPICE Simulation via Essential Parasitic Identification

Xin Jian, Jin Zhou, Tianjia Zhou, Jing‐Feng Li et al.
Semiconductor materials and devices
article

PiSPICE: Accelerating Post-Layout SPICE Simulation via Essential Parasitic Identification

Xin Jian, Jin Zhou, Tianjia Zhou, Jing‐Feng Li, Dan Niu, Xiao Wu, Zuochang Ye
article en

Abstract

As process nodes scale to more advanced technologies, post-layout simulations for integrated circuits have become increasingly complex, involving billions to trillions of nodes. The growing design complexity and transistor integration require more accurate and efficient post-layout SPICE simulations. However, existing methods for solving large-scale post-layout circuits face significant challenges due to high computational costs. In this paper, we propose a new approach, PiSPICE, which utilizes adjoint sensitivity analysis to identify critical parasitics and eliminate non-critical ones, effectively reducing the simulation scale and improving speed. By modeling parasitics and performing sensitivity analysis on pre-layout circuits, we significantly reduce the computational burden and avoid the overhead of directly analyzing sensitivities in large-scale postlayout circuits. By retaining only the critical parasitics and applying model order reduction to minimize their impact, while eliminating non-critical parasitics, PiSPICE achieves a speedup of up to 17.27 x in simulation with an error margin of less than 0.78% compared to the commercial simulator Spectre.

China University of Petroleum, Beijing (CN), DHC Software (China) (CN), Fraunhofer Institute for Integrated Circuits (DE), Southeast University (CN), Tsinghua University (CN)
Openalex Percentile: Top 76%
Semiconductor materials and devices
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

PiSPICE: Accelerating Post-Layout SPICE Simulation via Essential Parasitic Identification — Xin Jian, Jin Zhou, et al. · (2025) | TGRS Research Map | TGRS