Par4All: From Convex Array Regions to Heterogeneous Computing

Mehdi Amini (1) , Béatrice Creusillet (1, 2) , Stéphanie Even (3, 4) , Ronan Keryell (3, 5) , Onig Goubier (3) , Serge Guelton (3, 6) , Janice Onanian Mcmahon (3) , François-Xavier Pasquier (3) , Grégoire Péan (3) , Pierre Villalon (3)

1 CRI - Centre de Recherche en Informatique
2 Silkan
3 HPC PROJECT
4 HPCAS - HPCAS
5 LIT - Laboratoire Informatique et Télécommunications
6 INFO - Département informatique

Recent compilers comprise an incremental way for converting software toward accelerators. For instance, the pgi Accelerator [14] or hmpp [3] require the use of directives. The programmer must select the pieces of source that are to be executed on the accelerator, providing optional directives that act as hints for data allocations and transfers. The compiler generates all code automatically. [...] Unlike these approaches, Par4All [13] is an automatic parallelizing and optimizing compiler for C and Fortran sequential programs funded by the hpc Project startup. The purpose of this source-to-source compiler is to integrate several compilation tools into an easy-to-use yet powerful compiler that automatically transforms existing programs to target various hardware platforms.

Mots clés: OpenCL; Heterogeneous computing; convex array regions; source-to-source compilation; polyhedral model; gpu; cuda; OpenCL.

Domaines: Compilation; Parallélisation

Mehdi Amini, Béatrice Creusillet, Stéphanie Even, Ronan Keryell, Onig Goubier, et al.. Par4All: From Convex Array Regions to Heterogeneous Computing. IMPACT 2012 : Second International Workshop on Polyhedral Compilation Techniques HiPEAC 2012, Jan 2012, Paris, France. ⟨hal-00744733⟩