PIPS is an experhnental FORTRAN source-to-source parallelizer that combines the goal of exploring interprocedural and semantical analysis with a requirement for compilation speed.We present in this paper the main features of PIPS, i.e., demand-driven architecture, automatic support for multiple implementation languages, structured control graph, predicates and regions for interprocedural analysis and global nested loop paralle~lzation, with an emphasis on its core data structures and transformation phases.Some preliminary results on the practical impact of our design choices are discussed.

Supercompilers must reschedule computations defined by nested DO-loops in order to make an efficient use of supercomputer features (vector units, multiple elementary processors, cache memory, etc…). Many rescheduling techniques like loop interchange, loop strip-mining or rectangular partitioning have been described to speedup program execution. We present here a class of partitionings that encompasses previous techniques and provides enough flexibility to adapt code to multiprocessors with two levels of parallelism and two levels of memory.