Principle:Kubeflow Pipelines Parallel Iteration
| Sources | Domains | Last Updated |
|---|---|---|
| KFP Control Flow | ML_Pipelines, Control_Flow, Parallelism | 2026-02-13 |
Overview
A control flow pattern that executes the same set of tasks in parallel for each item in a collection, with optional concurrency limits.
Description
Parallel iteration (fan-out) distributes work by iterating over a list of items and executing contained tasks for each item concurrently. Items can be static (inline lists), structured (list of dicts with named fields), or dynamic (produced by a preceding component). A parallelism parameter controls the maximum number of concurrent iterations. Loop variables support attribute access for structured items.
Usage
Use for data-parallel workloads — hyperparameter sweeps, batch processing across data shards, or applying the same operation to multiple inputs.
Theoretical Basis
Map-style parallelism (fan-out/fan-in). Each item in the collection spawns an independent task execution. The parallelism parameter caps concurrent executions to manage resource consumption.