A programming framework pipelines data-parallel tasks in heterogeneous edge-cloud systems, enhancing efficiency.
We present SkePU-Streaming, a two-layer high-level programming framework for specifying complex pipelines composed of portable multi-backend stream processing tasks, each expressed by algorithmic skeletons or user-provided implementations, and its deployment toolchain for distributed heterogeneous parallel systems. Pipeline tasks can have multiple implementation variants to more flexibly exploit the resources of heterogeneous nodes; the convenient expression of multi-variant tasks is achieved by integrating the high-level C++-based skeleton programming framework SkePU with its multiple backends as the main method for portable programming of the stream-processing tasks. Concretely, SkePU-Streaming adds an abstraction layer for pipeline workflow specifications atop SkePU-based task specifications. It extends the SkePU data-container API with stream access operators for use within SkePU and other C++ task code. We present the SkePU-Streaming design and its implementation in a deployment framework for distributed heterogeneous parallel systems, and demonstrate its use with two different video processing applications.
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Svensson et al. (2026) studied this question.
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