Computational and mathematical models meet heterogeneous computing

Abstract

During the last decade, parallel programming has evolved in an unprecedent way. Fifteen years ago, the future of parallel computing seemed to consist on the advent of multicore processors composed by an ever‐increasing number in the core count per CPU, and their interconnection to form larger clusters. Programming models, such as OpenMP1 that allows to transform sequential C and Fortran codes into parallel versions with low effort, without requiring to explicitly handle threads or to share memory among them, seemed to be the winner choice in a world where computers would include more and more cores inside a single chip. Message‐passing paradigms, such as MPI,2 provided a solution to interconnect these computers in larger facilities.