gsd-execute-phase

Execute phase plans with dependency-aware parallel scheduling by orchestrating tasks into wave-based parallel groups, where dependency-aware task groups run in parallel while preserving execution order across waves to optimize throughput.

Wave-based parallelism in workflow orchestration groups dependency-aware tasks into sequential execution waves, allowing independent plans within each wave to run concurrently via subagents while maintaining correct dependency order across waves.

Run multiple subagents in parallel without breaking task dependencies by analyzing plan dependencies, grouping independent tasks into concurrent waves, and spawning subagents only for tasks whose dependencies are already satisfied.

This workflow orchestration approach supports automatic checkpointing and state recovery by preserving execution progress after each wave completes, enabling phase execution to resume from the last saved checkpoint state if interrupted.

Reduce latency when executing multi-phase workflows by grouping independent plans into parallel execution waves based on dependency analysis, maximizing concurrent subagent execution while preserving required ordering across waves.

You can use this wave-based execution for multi-phase workflows with complex dependency graphs because it performs plan discovery and dependency analysis to organize tasks into correctly ordered parallel waves, accommodating intricate dependency relationships.