18099083. SEMICONDUCTOR DEVICE SIMULATION SYSTEM AND METHOD simplified abstract (SAMSUNG ELECTRONICS CO., LTD.)
SEMICONDUCTOR DEVICE SIMULATION SYSTEM AND METHOD
Organization Name
Inventor(s)
SANG HOON Myung of SUWON-SI, (KR)
JAE MYUNG Choe of SUWON-SI (KR)
SEMICONDUCTOR DEVICE SIMULATION SYSTEM AND METHOD - A simplified explanation of the abstract
This abstract first appeared for US patent application 18099083 titled 'SEMICONDUCTOR DEVICE SIMULATION SYSTEM AND METHOD
Simplified Explanation
The patent application describes systems and methods for simulating a semiconductor device using a graph neural network (GNN) learning model. The process involves generating meshes associated with the simulated semiconductor device using a semiconductor device simulator. Nodes and edges are extracted from the information associated with the meshes, and graph information is generated based on these nodes and edges. The graph information is then applied to a GNN learning model. By applying state information to the simulated semiconductor device, the GNN learning model predicts changes in the meshes.
- The patent application describes a method for simulating a semiconductor device using a graph neural network (GNN) learning model.
- Meshes associated with the simulated semiconductor device are generated using a semiconductor device simulator.
- Nodes are extracted from the information associated with the meshes.
- Edges connected between the nodes are extracted using information associated with the meshes.
- Graph information is generated based on the nodes and edges.
- The graph information is applied to a GNN learning model.
- The GNN learning model predicts changes in the meshes in response to changes in state information applied to the simulated semiconductor device.
Potential Applications
- Semiconductor device simulation
- Semiconductor device design optimization
- Semiconductor device performance analysis
Problems Solved
- Accurate simulation of semiconductor devices
- Efficient prediction of changes in semiconductor device meshes
- Integration of graph neural network learning models in semiconductor device simulation
Benefits
- Improved accuracy in simulating semiconductor devices
- Faster prediction of changes in semiconductor device meshes
- Enhanced design optimization and performance analysis capabilities for semiconductor devices
Original Abstract Submitted
Systems and methods for simulating a semiconductor device, a method among includes; generating meshes associated with a simulated semiconductor device using a semiconductor device simulator, extracting nodes from information associated with the meshes, extracting edges connected between the nodes using information associated with the meshes, generating graph information in relation to the nodes and edges, applying the graph information to a graph neural network (GNN) learning model, and predicting change in the meshes in response to change in state information applied to the simulated semiconductor device using the GNN learning model.
