Erbium: A Deterministic, Concurrent Intermediate Representation to Map Data-Flow Tasks to Scalable, Persistent Streaming Processes

Cupertino Miranda 1 Antoniu Pop 2 Philippe Dumont 1, 3 Albert Cohen 1 Marc Duranton 3, 4
1 ALCHEMY - Architectures, Languages and Compilers to Harness the End of Moore Years
LRI - Laboratoire de Recherche en Informatique, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France, CNRS - Centre National de la Recherche Scientifique : UMR8623
2 CRI - Centre de Recherche en Informatique
3 NXP Semiconductors
4 LIST - Laboratoire d'Intégration des Systèmes et des Technologies
Abstract : Tuning applications for multicore systems involve subtle concurrency concepts and target-dependent optimizations. This paper advocates for a streaming execution model, called \ER, where persistent processes communicate and synchronize through a multi-consumer multi-producer sliding window. Considering media and signal processing applications, we demonstrate the scalability and efficiency advantages of streaming compared to data-driven scheduling. To exploit these benefits in compilers for parallel languages, we propose an intermediate representation enabling the compilation of data-flow tasks into streaming processes. This intermediate representation also facilitates the application of classical compiler optimizations to concurrent programs.
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Communication dans un congrès
International Conference on Compilers Architectures and Synthesis for Embedded Systems (CASES'10), Oct 2010, Scottsdale, United States. 11p, 2010
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Cupertino Miranda, Antoniu Pop, Philippe Dumont, Albert Cohen, Marc Duranton. Erbium: A Deterministic, Concurrent Intermediate Representation to Map Data-Flow Tasks to Scalable, Persistent Streaming Processes. International Conference on Compilers Architectures and Synthesis for Embedded Systems (CASES'10), Oct 2010, Scottsdale, United States. 11p, 2010. 〈inria-00551510〉

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