The aim of this Thesis was to study Processing-in-Memory (PIM) architectures, in current Exascale Computing and Big Data era, exploiting a structured approach and a methodology able to capture all the useful details to carry out a performance, as well as energy, characterization of structured parallel programs targeting PIM systems
