A methodology for programming scalable architectures

In scalable concurrent architectures, the performance of a parallel algorithm depends on the resource management policies used. Such policies determine, for example, how data is partitioned and distributed and how processes are scheduled. In particular, the performance of a parallel algorithm obtained by using a particular policy can be affected by increasing the size of the architecture or the input. In order to support scalability, we are developing a methodology for modular specification of partition and distribution strategies (PDSs). As a consequence, a PDS may be changed without modifying the code specifying the logic of a parallel algorithm. We illustrate our methodology for parallel algorithms that use dynamic data structures.