SAGA: State-Aware Graph Analytics for Combinatorial Optimization on Dynamic Graphs
This work presents SAGA, a high-performance framework for real-time combinatorial optimization on dynamic graphs that adopts a state-aware execution model in which each vertex maintains compact local state, enabling incremental and localized updates in response to graph changes.