Jian Xin

dblp:348/3368 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Electronic design automation · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Electronic design automation
circuit simulation
0.912025
PiSPICE: Accelerating Post-Layout SPICE Simulation via Essential Parasitic Identification · DAC 2025
Electronic design automation › physical design
parasitic extraction
0.912025
PiSPICE: Accelerating Post-Layout SPICE Simulation via Essential Parasitic Identification · DAC 2025
Electronic design automation › circuit simulation
post-layout simulation
0.912025
PiSPICE: Accelerating Post-Layout SPICE Simulation via Essential Parasitic Identification · DAC 2025
Electronic design automation › circuit simulation › analog circuit simulation
SPICE simulation
0.912025
PiSPICE: Accelerating Post-Layout SPICE Simulation via Essential Parasitic Identification · DAC 2025
Electronic design automation › circuit simulation
model order reduction
0.312025
PiSPICE: Accelerating Post-Layout SPICE Simulation via Essential Parasitic Identification · DAC 2025

Methods — techniques the papers use, named apart from their topics

adjoint sensitivity analysis · 0.9
YearPublicationVenuePosition
2025 PiSPICE: Accelerating Post-Layout SPICE Simulation via Essential Parasitic Identification
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.
Jian Xin, Tianjia Zhou, Dan Niu, Zuochang Ye
DAC3