Parallel.ForEach or Task.Factory.StartNew: Which Offers Better Performance in C# Parallel Programming?

C# Parallel Programming: Parallel.ForEach and Task.Factory.StartNew Performance Analysis

In C# parallel programming, developers often need to choose whether to use Parallel.ForEach or Task.Factory.StartNew. Both can process items in a collection in parallel, but differ in key ways that impact performance and resource utilization.

Parallel execution comparison

Parallel.ForEach uses Partitioner to distribute collections into work items. This approach minimizes overhead by batching projects rather than creating separate tasks for each project. This efficiency is especially significant for large collections, reducing runtime and reducing the need for thread pool threads.

In contrast, Task.Factory.StartNew schedules a task for each item in the collection. While the results are similar, the overhead it introduces becomes significant for large collections, resulting in slower execution times.

Synchronized behavior

Another key difference is synchronization. Parallel.ForEach executes synchronously by default, which means it blocks the calling thread until the operation completes. To implement asynchronous execution, you can use Task.Factory.StartNew() to wrap Parallel.ForEach.

Other considerations

For advanced scenarios, Parallel.ForEach allows customizing the Partitioner used through various overloads. This control allows developers to tailor partitioning strategies to specific needs.

Conclusion

When choosing between Parallel.ForEach and Task.Factory.StartNew, the main considerations are performance and synchronization. For parallel operations on large collections, Parallel.ForEach provides greater efficiency by minimizing overhead and leveraging partitioning. For scenarios that require asynchronous execution, wrapping Parallel.ForEach with Task.Factory.StartNew() can provide flexibility while maintaining the advantages of partitioning.

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