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To be effectively implemented, data pipelines need a CPU [[scheduling]] strategy to dispatch work to the available CPU cores, and the usage of [[data structures]] on which the pipeline stages will operate on. For example, [[UNIX]] derivatives may pipeline commands connecting various processes' standard IO, using the pipes implemented by the operating system.
Lower level approaches may rely on the threads provided by the operating system to schedule work on the stages: both [[thread pool]]-based implementations or on a one-thread-per-stage are viable, and exist.<ref>{{cite web | url=https://github.com/dteod/mtdp.git/
Other strategies relying on [[cooperative multitasking]] exist, that do not need multiple threads of execution and hence additional CPU cores, such as using a round-robin scheduler with a coroutine-based framework. In this context, each stage may be instantiated with its own coroutine, yielding control back to the scheduler after finishing its round task. This approach may need careful control over the process' stages to avoid them abuse their time slice.
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