Execution Graph

The breakdown of a function into tasks is represented as a directed acyclic graph (DAG), called the execution graph. The graph consists of:

• Nodes (Tasks): Each task in the function is a node in the graph.

• Edges (Dependencies): Directed edges between tasks represent dependencies, meaning one task must be completed before another can start.

Execution graph example

Key Features of the Execution Graph

1. Dynamic Refinement: The orchestration layer can break tasks into smaller subtasks if needed, allowing for more flexible and efficient scheduling.

2. Instruction Expansion: Composite instructions within tasks can be expanded into their atomic components, ensuring they can be executed by available resources.

This adaptability allows the system to optimize task execution based on available resources and workload while maintaining proper dependency order.