Name
Title | ||
|---|---|---|
Model Driven Iterative Multi-dimensional Parallelization of Multi-task Programs for the Cell BE: A Genetic Algorithm-Based Approach |
Abstract | ||
|---|---|---|
Multicore processor architectures provide huge computation power by leveraging multiple levels of parallelism. However, it is non-trivial to orchestrate computational and memory resources allocation on the multicore platform. In this paper, we model the resources allocation for multicores as an optimization space, including variant selection, grouping and PE assignment. Finding efficient parallelization schemes for a multi-task program is to explore this search space. In order to accelerate the space exploration, we adapt genetic algorithm to find out the performance optimal solutions. Experiments are conducted on the Cell BE using two benchmarks. Compared to exhaustive enumeration, the intelligent search based on genetic algorithm can derive good parallelization schemes in very short time. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/PDP.2010.42 | PDP |
Keywords | Field | DocType |
model driven iterative multi-dimensional,multitask programs,model driven iterative multidimensional parallelization,genetic algorithm-based approach,memory resources allocation,microprocessor chips,multicore processor architectures,cell be,parallel architectures,optimization space,resources allocation,exhaustive enumeration,efficient parallelization scheme,resource allocation,good parallelization scheme,variant selection,performance optimal solutions,memory resource allocation,multiprocessing systems,multiprocessing programs,genetic algorithm,multicore platform,genetic algorithms,space exploration,intelligent search,multi-task programs,search space,iterative methods,multicore processor architecture,optimization,computational modeling,resource management,computer architecture,parallel processing,multicore processors | Resource management,Iterative method,Computer science,Parallel computing,Space exploration,Resource allocation,Multi-core processor,Genetic algorithm,Automatic parallelization,Computation | Conference |
ISSN | ISBN | Citations |
1066-6192 E-ISBN : 978-1-4244-5673-4 | 978-1-4244-5673-4 | 0 |
PageRank | References | Authors |
0.34 | 1 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Miao Wang | 1 | 8 | 2.93 |
| Nicolas Benoit | 2 | 1 | 0.70 |
| Francois Bodin | 3 | 54 | 4.85 |
| Zhi-Ying Wang | 4 | 870 | 127.04 |