Results Publications

Programming models for task-based parallelization based on compile-time directives are very effective at uncovering the parallelism available in HPC applications. Despite that, the process of correctly annotating complex applications is error-prone and may hinder the general adoption of these models. In this paper, we target the OmpSs-2 programming model and present a novel toolchain able to detect parallelization errors coming from non-compliant OmpSs-2 applications. Our toolchain verifies the compliance with the OmpSs-2 programming model using local task analysis to deal with each task separately, and structural induction to extend the analysis to the whole program. To improve the effectiveness of our tools, we also introduce some ad-hoc verification annotations, which can be used manually or automatically to disable the analysis of specific code regions. Experiments run on a sample of representative kernels and applications show that our toolchain can be successfully used to verify the parallelization of complex real-world applications.