Towards Automatic Parallelization of Stream Processing Applications
Scholar | Other documents of the author: Dolz, Manuel F.; del Río Astorga, David; Fernández Muñoz, Javier; García, J. Daniel; Carretero, Jesús
MetadataShow full item record
TitleTowards Automatic Parallelization of Stream Processing Applications
Parallelizing and optimizing codes for recent multi-/many-core processors have been recognized to be a complex task. For this reason, strategies to automatically transform sequential codes into parallel and discover ... [+]
Parallelizing and optimizing codes for recent multi-/many-core processors have been recognized to be a complex task. For this reason, strategies to automatically transform sequential codes into parallel and discover optimization opportunities are crucial to relieve the burden to developers. In this paper, we present a compile-time framework to (semi) automatically find parallel patterns (Pipeline and Farm) and transform sequential streaming applications into parallel using GrPPI, a generic parallel pattern interface. This framework uses a novel pipeline stage-balancing technique which provides the code generator module with the necessary information to produce balanced pipelines. The evaluation, using a synthetic video benchmark and a real-world computer vision application, demonstrates that the presented framework is capable of producing parallel and optimized versions of the application. A comparison study under several thread-core oversubscribed conditions reveals that the framework can bring comparable performance results with respect to the Intel TBB programming framework. [-]
Investigation projectSpanish Ministerio de Economía y Competitividad, Project Toward Unification of HPC and Big Data Paradigms (Grant TIN2016-79637-P) ; EU Project RePhrase: REfactoring Parallel Heterogeneous Resource-Aware Applications (Grant ICT 644235).
Bibliographic citationDOLZ, Manuel F., et al. Towards Automatic Parallelization of Stream Processing Applications. IEEE Access, 2018, 6: 39944-39961.
© Copyright 2018 IEEE - All rights reserved.
This item appears in the folowing collection(s)
- ICC_Articles