The need for features for managing complex data accesses in modern programming models has increased due to the emerging hardware architectures. HPC hardware has moved towards clusters of accelerators and/or multicores, architectures with a complex memory hierarchy exposed to the programmer. We present the implementation of data regions on the OmpSs programming model, a high-productivity annotation-based programming model derived from OpenMP. This enables the programmer to specify regions of strided and/or overlapped data used by the parallel tasks of the application. The data will be automatically managed by the underlying run-time environment, which could transparently apply optimization techniques to improve performance. This approach based on a high-productivity programming model contrasts with more direct approaches like MPI, where the programmer has to explicitly deal with the data management. It is generally believed that these are capable of achieving the best possible performance, so we also compare the performance of several OmpSs applications against well-known counterparts MPI implementations obtaining comparable or better results.

We thankfully acknowledge the support of the European Commission through the ENCORE project (FP7-248647), the TERAFLUX project (FP7-249013), the TEXT project (FP7-261580), and the HiPEAC-3 Network of Excellence (ICT FP7 NoE 287759), the support of the Spanish Ministry of Science and Technology (TIN2007-60625, TIN2012-34557, CSD2007-00050 and FPU program) and the Generalitat de Catalunya (2009-SGR-980

Peer Reviewed