A low level component model easing performance portability of HPC applications

Abstract

Scientific applications are getting increasingly complex, e.g., to improve their accuracy by taking into account more phenomena. Meanwhile, computing infrastructures are continuing their fast evolution. Thus, software engineering is becoming a major issue to offer ease of development, portability and maintainability while achieving high performance. Component based software engineering offers a promising approach that enables the manipulation of the software architecture of applications. However, existing models do not provide an adequate support for performance portability of HPC applications. This paper proposes a low level component model (L $$^2$$ C) that supports inter-component interactions for typical scenarios of high performance computing, such as process-local shared memory and function invocation (C++ and Fortran), MPI, and Corba. To study the benefits of using L $$^2$$ C, this paper walks through an example of stencil computation, i.e. a structured mesh Jacobi implementation of the 2D heat equation parallelized through domain decomposition. The experimental results obtained on the Grid’5000 testbed and on the Curie supercomputer show that L $$^2$$ C can achieve performance similar to that of native implementations, while easing performance portability.