TPL Dataflow (Task Parallel Library)

This dataflow model promotes actor-based programming by providing in-process message passing for coarse-grained dataflow and pipelining tasks. The TPL Dataflow Library provides a foundation for message passing and parallelizing CPU-intensive and I/O-intensive applications that have high throughput and low latency. It also gives you explicit control over how data is buffered and moves around the system. Because the runtime manages dependencies between data, you can often avoid the requirement to synchronize access to shared data. In addition, because the runtime schedules work based on the asynchronous arrival of data, dataflow can improve responsiveness and throughput by efficiently managing the underlying threads. 

MSDN Dataflow (Task Parallel Library)

Predefined dataflow block types are divided into three categories: buffering blocks, execution blocks, and grouping blocks.

Buffering Blocks 

• BufferBlock
• BroadcastBlock
• WriteOnceBlock

Execution Blocks

• ActionBlock
• TransformBlock
• TransformManyBlock

Grouping Blocks

• BatchBlock
• JoinBlock
• BatchedJoinBlock