ABSTRACT
OpenMP seems to be the easiest way to write parallel programs as it features a simple, directive-based interface and incremental parallelization, meaning that the loops of a program can be tackled one by one without major code restructuring. It turns out, however, that getting a truly scalable OpenMP program is a significant undertaking in all but the most trivial cases. This chapter pinpoints some of the performance problems that can arise with OpenMP shared-memory programming and how they can be circumvented. We then turn to the OpenMP parallelization of the sparse MVM code that has been introduced in Chapter 3.
