anyflow
is a component-based parallel computing framework that achieves parallelism by breaking down a computing task into a series of sub-tasks, which are then organized in a Directed Acyclic Graph (DAG).
Unlike traditional DAG-based parallel frameworks, in anyflow
, the sub-tasks are not directly connected. Instead, the framework introduces the concept of data nodes to explicitly represent the data flow between sub-tasks. This explicit data flow representation eliminates implicit data dependencies between sub-tasks, reducing the coupling between them. Moreover, through the intermediary data nodes, anyflow
enables advanced features such as partial execution, conditional execution, and micro-pipeline interaction.