EDA platform operation and maintenance method, system, device and readable storage medium
By constructing a three-level digital twin model and license-aware reinforcement learning, the problems of resource conflicts and unreproducible signing results in EDA computing clusters are solved, realizing a unified platform for intelligent operation and maintenance and traceable and reproducible results.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SUZHOU HUAXIN MICROELECTRONICS
- Filing Date
- 2026-05-26
- Publication Date
- 2026-07-14
AI Technical Summary
Existing EDA computing cluster operation and maintenance technologies cannot detect micro-architectural resource conflicts such as memory and bandwidth contention, and lack fine-grained forward-looking optimization for expensive EDA licenses, resulting in idleness and deadlock; the signing results are unreproducible due to dependence on drift and environmental differences, and lack automated consistency determination and difference attribution.
A three-tiered digital twin model is constructed, which combines a memory bandwidth contention model to quantify resource conflicts. A license-aware reinforcement learning and rule masking mechanism is introduced to generate optimal scheduling instructions. Environment reconstruction is achieved through snapshot records and reproduction packages to ensure that the results are traceable and reproducible.
It achieves accurate prediction and avoidance of microarchitectural resource conflicts, avoids ineffective scheduling and deadlocks, ensures consistent reproduction of approval results and automated attribution of differences, and forms a unified intelligent operation and maintenance platform covering design, operation and approval verification.
Smart Images

Figure CN122389773A_ABST