Barcelona Supercomputing Center

Abstract—As new heterogeneous systems and hardware ac-celerators appear, high performance computers can reach a higher level of computational power. Nevertheless, this does not come for free: the more heterogeneity the system presents, the more complex becomes the programming task in terms of resource management. OmpSs is a task-based programming model and framework focused on the runtime exploitation of parallelism from an-notated sequential applications. This paper presents a set of extensions to this framework: we show how the application programmer can expose different specialized versions of tasks (i.e. pieces of specific code targeted and optimized for a par-ticular architecture) and how the system can choose between these versions at runtime to obtain the best performance achievable for the given application. From the results obtained in a multi-GPU system, we prove that our proposal gives flexibility to application’s source code and can potentially increase application’s performance. Keywords-multi-gpu management; heterogeneous architec-tures; parallel programming models; scheduling techniques I