Supporting high-performance computing pipelines in wide-area networks is crucial to enabling large-scale distributed scientific applications that require minimizing end-to-end delay for fast user interaction or maximizing frame rate for smooth data flow. We formulate and categorize the linear pipeline configuration problems into six classes with two mapping objectives, i.e. minimum end-to-end delay and maximum frame rate, and three network constraints, i.e. no, contiguous, and arbitrary node reuse. We design a dynamic programming-based optimal solution to the configuration problem for minimum end-to-end delay with arbitrary node reuse and prove the NP-completeness of the rest five problems, for each of which, a heuristic algorithm based on a similar optimization procedure is proposed. Performance superiorities of these heuristics are illustrated by extensive experimental results in comparison with existing methods.