dag-task-scheduler

What problem does it solve?

Scheduling and coordinating large DAGs with many tasks is complex and often limited by resource contention and dependency constraints. The DAG Task Scheduler provides wave-based execution plans that maximize concurrency while respecting CPU, memory, and timing constraints.

Core Features & Use Cases

• Wave-based scheduling groups independent tasks into parallel waves to maximize throughput while preserving dependencies.
• Adaptive scheduling supports runtime feedback, early completion, and dynamic rescheduling to maintain efficiency.
• Resource-aware planning allocates budgets and enforces limits to prevent contention and bottlenecks in complex workflows.
• Use Case: orchestrating a data processing pipeline where stages can run concurrently after dependencies are satisfied.

Quick Start

Provide a sample DAG and run the scheduler to generate a wave-based execution plan.