Supporting scientists in re-engineering sequential programs to parallel using model-driven engineering
Contribuinte(s) |
Carver, J. Ciancarini, P. Hong, N.C. |
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Data(s) |
01/01/2015
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Resumo |
Developing complex computational-intensiveand data-intensive scientific applications requires effectiveutilization of the computational power of the availablecomputing platforms including grids, clouds, clusters, multicoreand many-core processors, and graphical processingunits (GPUs). However, scientists who need to leverage suchplatforms are usually not parallel or distributed programmingexperts. Thus, they face numerous challenges whenimplementing and porting their software-based experimentaltools to such platforms. In this paper, we introduce asequential-to-parallel engineering approach to help scientistsin engineering their scientific applications. Our approach isbased on capturing sequential program details, plannedparallelization aspects, and program deployment details usinga set of domain-specific visual languages (DSVLs). Then, usingcode generation, we generate the corresponding parallelprogram using necessary parallel and distributedprogramming models (MPI, OpenCL, or OpenMP). Wesummarize three case studies (matrix multiplication, N-Bodysimulation, and signal processing) to evaluate our approach. |
Identificador | |
Idioma(s) |
eng |
Publicador |
IEEE |
Relação |
http://dro.deakin.edu.au/eserv/DU:30082726/almorsy-supportingscientists-2015.pdf http://dro.deakin.edu.au/eserv/DU:30082726/almorsy-supportingscientists-evid-2015.pdf http://www.dx.doi.org/10.1109/SE4HPCS.2015.8 |
Direitos |
2015, IEEE |
Palavras-Chave | #Parallel programming #High-performance computing #Domain-specific visual language |
Tipo |
Conference Paper |