VLSI System Computing Lab (VSCLAB)
VSCLAB introduction
VLSI System Computing Lab (VSCLAB) is directed by Prof. Sheldon Tan, who is a Professor at Department of Electrical and Computer Engineering at Bourns College of Engineering. Dr. Tan is also a cooperating faculty member (co-faculty) of the Computer Science and Engineering department. Here are his latest curriculum vitae and short biography and my publication list.
In addition, Dr. Tan is the Editor in Chief (EIC) of Integration, The VLSI Journal, which is one of the primary journals in the VLSI design and CAD/design automation (EDA) areas with CiteScore 3.8 and IF 2.2 (as of 2024). Welcome to submit your papers to this journal.
VSCLAB Recent Research Highlights:
- EMspice: coupled EM-IR analysis tool for full-chip power grid EM and IR check and sign-off
- GPU-accelerated sparse parallel LU factorization solver project, GLU V3.0 is available in Github now (with sources codes and examples)
- The new physics-based EM model for more accurate EM assessment and EM signoff
Current research areas
- Machine and deep learning for VLSI reliability modeling and optimization
- Advanced VLSI design techniques for machine and deep learnings
- VLSI long-term reliability, resilient systems, fault tolerant computing, reliability-aware design and management at circuit and system levels
- Machine learning based thermal modeling, optimization and dynamic thermal management at circuit, chip and board levels
- Parallel computing and analysis on heterogeneous and accelerator-rich (GPUs) platforms
- Statistic modeling and optimization for VLSI systems
We appreciate support from the following sponsors
Latest News from VSCLAB
Ph.D. student Mohammadamir (Amir) Kavousi successfully defended their thesis, titled " Physics-Based Modeling of Coupled Electromigration and Thermomigration in Multi-Segment Interconnects considering Joule Heating Effects". Best wishes for his future endeavors!
The job openings in VSCLAB
My group now has 2-3 Ph.D. openings for the Fall 2025. Students with electrical engineering, computer science, physics and applied mathematics backgrounds are welcome to apply. Students with M.S. degrees are preferred. Full financial supports will be provided for qualified students.