Semiconductors
Quantum-Ready Simulation for Next-Generation Chip Design
With ColibriTD’s hybrid quantum-classical platform QUICK, semiconductor engineers can accelerate multiphysics simulations, detect anomalies early, and optimize chip design, preparing for quantum-enhanced semiconductor modeling.
Quickly navigate through the use cases
1.
Early Anomaly Detection in Microchips
Traditional IR drop analysis struggles to balance accuracy, speed, and scalability. Full-chip simulations can take days to weeks, scaling cubically with circuit size, while sometimes missing worst-case voltage scenarios, a problem that worsens as transistors shrink.
H-DES simulates complex multi-physics phenomena at the nanoscale using a hybrid quantum-classical approach, enabling early detection of voltage and reliability anomalies while keeping classical methods for overall analysis.
Impact
.jpeg)
Gain time
Faster full-chip reliability simulations
.jpeg)
Improve detection
Improved detection of worst-case scenarios
.jpeg)
Improve design
Enhanced confidence in design correctness and yield
2.
Thermal and Electromigration Modeling
As transistor densities increase, localized heating and current crowding create thermal hotspots and electromigration risks, threatening performance and lifetime.
H-DES models coupled thermal, electrical, and material stress phenomena, predicting hotspots and material degradation across the chip.
Impact
.jpeg)
Improve accuracy
Accurate identification of thermal and stress bottlenecks
.jpeg)
Optimize design
Optimized layout and interconnect design

Reduce risk
Reduced risk of premature failures and costly redesigns
3.
Advanced Power and Signal Integrity Analysis
High-frequency circuits, multi-core processors, and complex IC architectures require precise power and signal integrity analysis under dynamic conditions. Classical methods struggle to simulate large-scale interactions quickly.
H-DES solves large-scale PDEs for voltage, current, and signal propagation, enabling rapid evaluation of power integrity, IR drop, and noise margins across the entire chip.
Impact
.jpeg)
Gain time
Faster verification of power delivery networks
.jpeg)
Improve accuracy
Improved accuracy for signal integrity and timing analysis
.jpeg)
Improve performance
Enhanced chip performance and reliability

.png)

.png)




