AI/ML algorithms and applications in VLSI design and technology
An evident challenge ahead for the integrated circuit (IC) industry is the investigation and
development of methods to reduce the design complexity ensuing from growing process …
development of methods to reduce the design complexity ensuing from growing process …
High-definition routing congestion prediction for large-scale FPGAs
To speed up the FPGA placement and routing closure, we propose a novel approach to
predict the routing congestion map for large-scale FPGA designs at the placement stage …
predict the routing congestion map for large-scale FPGA designs at the placement stage …
GeniusRoute: A new analog routing paradigm using generative neural network guidance
Due to sensitive layout-dependent effects and varied performance metrics, analog routing
automation for performance-driven layout synthesis is difficult to generalize. Existing …
automation for performance-driven layout synthesis is difficult to generalize. Existing …
Powernet: SOI lateral power device breakdown prediction with deep neural networks
The breakdown performance is a critical metric for power device design. This paper explores
the feasibility of efficiently predicting the breakdown performance of silicon on insulator (SOI) …
the feasibility of efficiently predicting the breakdown performance of silicon on insulator (SOI) …
Machine learning-based edge placement error analysis and optimization: a systematic review
As the semiconductor manufacturing process is moving towards the 3 nm node, there is a
crucial need to reduce the edge placement error (EPE) to ensure proper functioning of the …
crucial need to reduce the edge placement error (EPE) to ensure proper functioning of the …
GridNet: Fast data-driven EM-induced IR drop prediction and localized fixing for on-chip power grid networks
Electromigration (EM) is a major failure effect for on-chip power grid networks of deep
submicron VLSI circuits. EM degradation of metal grid lines can lead to excessive voltage …
submicron VLSI circuits. EM degradation of metal grid lines can lead to excessive voltage …
Full-chip thermal map estimation for commercial multi-core CPUs with generative adversarial learning
In this paper, we propose a novel transient full-chip thermal map estimation method for multi-
core commercial CPU based on the data-driven generative adversarial learning method. We …
core commercial CPU based on the data-driven generative adversarial learning method. We …
DeePattern: Layout pattern generation with transforming convolutional auto-encoder
VLSI layout patterns provide critic resources in various design for manufacturability
researches, from early technology node development to back-end design and sign-off flows …
researches, from early technology node development to back-end design and sign-off flows …
Em-gan: Data-driven fast stress analysis for multi-segment interconnects
Electromigration (EM) analysis for complicated interconnects requires the solving of partial
differential equations, which is expensive. In this paper, we propose a fast transient …
differential equations, which is expensive. In this paper, we propose a fast transient …
Adversarial perturbation attacks on ML-based CAD: A case study on CNN-based lithographic hotspot detection
There is substantial interest in the use of machine learning (ML)-based techniques
throughout the electronic computer-aided design (CAD) flow, particularly those based on …
throughout the electronic computer-aided design (CAD) flow, particularly those based on …