Abstract:Heterogeneous systems, consisting of CPUs and GPUs, offer the capability to address the demands of compute-and data-intensive applications. However, programming such systems is challenging, requiring knowledge of various parallel programming frameworks. This paper introduces COMPAR, a component-based parallel programming framework that enables the exposure and selection of multiple implementation variants of components at runtime. The framework leverages compiler directive-based language extensions to annotate… Show more
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