A two-level GNN with temperature sampling inside a Generate-and-Verify loop synthesizes enforceable, system-schedulable JLDs for cause-effect chains faster and more successfully than the prior greedy heuristic.
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Schedulable Job-Level Dependencies for Cause-Effect Chains via Graph Neural Networks
A two-level GNN with temperature sampling inside a Generate-and-Verify loop synthesizes enforceable, system-schedulable JLDs for cause-effect chains faster and more successfully than the prior greedy heuristic.