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Pipeline is a fundamental parallel programming pattern. Mainstream pipelineprogramming frameworks count on data abstractions to perform pipelinescheduling. This design is convenient for data-centric pipeline applicationsbut inefficient for algorithms that only exploit task parallelism in pipeline.As a result, we introduce a new task-parallel pipeline programming frameworkcalled Pipeflow. Pipeflow does not design yet another data abstraction butfocuses on the pipeline scheduling itself, enabling more efficientimplementation of task-parallel pipeline algorithms than existing frameworks.We have evaluated Pipeflow on both micro-benchmarks and real-worldapplications. As an example, Pipeflow outperforms oneTBB 24% and 10% faster ina VLSI placement and a timing analysis workloads that adopt pipelineparallelism to speed up runtimes, respectively.

Pipeflow: An Efficient Task-Parallel Pipeline Programming Framework using Modern C++