A Novel Data-Centric Programming Model for Large-Scale Parallel Systems
| Autor: | Javier Garcia-Blas, Adrian Spataru, Lionel Vincent, David del Rio, Paolo Trunfio, Daniel Martín de Blas, Loris Belcastro, Alberto Fernández-Pena, Marek Justyna, Fabrizio Marozzo, Mirko Nardi, Philippe Couvee, Gael Goret, Domenico Talia, Teresa Pizzuti |
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| Rok vydání: | 2020 |
| Předmět: |
020203 distributed computing
Computer science 02 engineering and technology Parallel computing Thread (computing) Scalable parallelism Data structure Exascale computing Database-centric architecture Synchronization (computer science) 0202 electrical engineering electronic engineering information engineering Programming paradigm 020201 artificial intelligence & image processing Partitioned global address space |
| Zdroj: | Euro-Par 2019: Parallel Processing Workshops ISBN: 9783030483395 Euro-Par Workshops |
| DOI: | 10.1007/978-3-030-48340-1_35 |
| Popis: | This paper presents the main features and the programming constructs of the DCEx programming model designed for the implementation of data-centric large-scale parallel applications on Exascale computing platforms. To support scalable parallelism, the DCEx programming model employs private data structures and limits the amount of shared data among parallel threads. The basic idea of DCEx is structuring programs into data-parallel blocks to be managed by a large number of parallel threads. Parallel blocks are the units of shared- and distributed-memory parallel computation, communication, and migration in the memory/storage hierarchy. Threads execute close to data using near-data synchronization according to the PGAS model. A use case is also discussed showing the DCEx features for Exascale programming. |
| Databáze: | OpenAIRE |
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