Performance Behavior Prediction Scheme for Shared-Memory Parallel Applications

2011 ◽  
Author(s):  
John Corredor ◽  
Juan Carlos Moure ◽  
Dolores Rexachs ◽  
Daniel Franco ◽  
Emilio Luque
Keyword(s):  
Shared Memory ◽  
Parallel Applications ◽  
Behavior Prediction ◽  
Prediction Scheme ◽  
Performance Behavior

scholarly journals SPar: A DSL for High-Level and Productive Stream Parallelism

2017 ◽  
Vol 27 (01) ◽  
pp. 1740005 ◽  
Author(s):  
Dalvan Griebler ◽  
Marco Danelutto ◽  
Massimo Torquati ◽  
Luiz Gustavo Fernandes
Keyword(s):  
Shared Memory ◽  
Stream Processing ◽  
Parallel Applications ◽  
Domain Specific Language ◽  
Specific Language ◽  
Domain Specific ◽  
Implementation Techniques ◽  
High Level

This paper introduces SPar, an internal C++ Domain-Specific Language (DSL) that supports the development of classic stream parallel applications. The DSL uses standard C++ attributes to introduce annotations tagging the notable components of stream parallel applications: stream sources and stream processing stages. A set of tools process SPar code (C++ annotated code using the SPar attributes) to generate FastFlow C++ code that exploits the stream parallelism denoted by SPar annotations while targeting shared memory multi-core architectures. We outline the main SPar features along with the main implementation techniques and tools. Also, we show the results of experiments assessing the feasibility of the entire approach as well as SPar’s performance and expressiveness.

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