Self-adaptive OmpSs tasks in heterogeneous environments
Tipus de documentText en actes de congrés
EditorInstitute of Electrical and Electronics Engineers (IEEE)
Condicions d'accésAccés obert
As new heterogeneous systems and hardware accelerators 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 annotated 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 particular 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.
CitacióPlanas, J. [et al.]. Self-adaptive OmpSs tasks in heterogeneous environments. A: IEEE International Parallel and Distributed Processing Symposium. "IEEE 27th International Parallel and Distributed Processing Symposium: 20–24 May 2013, Boston, Massachusetts: proceedings". Boston, MA: Institute of Electrical and Electronics Engineers (IEEE), 2013, p. 138-149.