Transformer Surrogate Model for Circuit Path Embedding

The patent creates a surrogate model that copies the functionality of traditional software simulators. This surrogate model is trained on simulation data to replicate circuit evaluation behavior, enabling fast predictions without running full simulations. The model learns to approximate simulator outputs, achieving orders of magnitude speedup while maintaining acceptable accuracy for design exploration.

The patent performs preliminary actions by pre-training the surrogate model on extensive simulation data before actual circuit evaluations. During this offline training phase, the model learns patterns and relationships from thousands of simulated circuits. When deployed, the pre-trained model can rapidly evaluate new circuits without requiring time-consuming simulations, as the heavy computational work was already done during training.

The surrogate model serves as a computational copy that replicates simulator functionality with much lower resource requirements. Once trained, the model can evaluate circuits using minimal computational resources compared to full simulations, enabling high-throughput evaluation of large circuit spaces without proportionally increasing energy consumption.

The patent employs a computationally inexpensive surrogate model that can be rapidly deployed and executed. Unlike expensive, resource-intensive simulations, the surrogate model requires minimal computational power per evaluation, allowing thousands of circuits to be assessed with modest hardware resources and lower energy consumption.

The surrogate model creates a simplified copy of the simulation process that captures essential performance relationships. By learning from training data, the model reproduces key performance metrics without requiring the full computational complexity of detailed simulations, achieving acceptable precision for design optimization while dramatically reducing evaluation time.

The patent applies partial action by having the surrogate model predict only the most critical performance metrics rather than performing complete, exhaustive simulations. The model focuses on capturing dominant performance characteristics that matter for design decisions, sacrificing minor details in exchange for rapid evaluation capability across large circuit spaces.