PIPS Is not (just) Polyhedral Software Adding GPU Code Generation in PIPS
| Autor: | Amini, Mehdi, Ancourt, Corinne, Coelho, Fabien, Creusillet, Béatrice, Guelton, Serge, Irigoin, François, Jouvelot, Pierre, Keryell, Ronan, Villalon, Pierre |
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| Přispěvatelé: | Centre de Recherche en Informatique (CRI), MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), HPC PROJECT, HPC Project, Silkan, silkan, Département informatique (INFO), Université européenne de Bretagne - European University of Brittany (UEB)-Télécom Bretagne-Institut Mines-Télécom [Paris] (IMT), Laboratoire Informatique et Télécommunications (LIT), Ecole Nationale Supérieure des Télécommunications de Bretagne, Medrala, Claire |
| Jazyk: | angličtina |
| Rok vydání: | 2011 |
| Předmět: | |
| Zdroj: | First International Workshop on Polyhedral Compilation Techniques (IMPACT 2011) in conjonction with CGO 2011 First International Workshop on Polyhedral Compilation Techniques (IMPACT 2011) in conjonction with CGO 2011, Apr 2011, Chamonix, France |
| Popis: | 6 pages; International audience; Parallel and heterogeneous computing are growing in audience thanks to the increased performance brought by ubiquitous manycores and GPUs. However, available programming models, like OPENCL or CUDA, are far from being straightforward to use. As a consequence, several automated or semi-automated approaches have been proposed to automatically generate hardware-level codes from high-level sequential sources. Polyhedral models are becoming more popular because of their combination of expressiveness, compactness, and accurate abstraction of the data-parallel behaviour of programs. These models provide automatic or semi-automatic parallelization and code transformation capabilities that target such modern parallel architectures. PIPS is a quarter-century old source-to-source transformation framework that initially targeted parallel machines but then evolved to include other targets. PIPS uses abstract interpretation on an integer polyhedral lattice to represent program code, allowing linear relation analysis on integer variables in an interprocedural way. The same representation is used for the dependence test and the convex array region analysis. The polyhedral model is also more classically used to schedule code from linear constraints. In this paper, we illustrate the features of this compiler infrastructure on an hypothetical input code, demonstrating the combination of polyhedral and non polyhedral transformations. PIPS interprocedural polyhedral analyses are used to generate data transfers and are combined with non-polyhedral transformations to achieve efficient CUDA code generation. |
| Databáze: | OpenAIRE |
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