Automatic parallel code generation for message passing on distributed memory systems

The availability of a very accurate dependence graph for a scalar code is the basis for the automatic generation of an efficient parallel implementation. The strategy for this task which is encapsulated in a comprehensive data partitioning code generation algorithm is described. This algorithm invol...

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Vydané v:Parallel computing Ročník 22; číslo 2; s. 227 - 258
Hlavní autori: Johnson, S.P., Ierotheou, C.S., Cross, M.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier B.V 1996
Predmet:
Automatic parallel code generation
Interprocedural dependence analysis
Parallelisation tools
Parallelisation tools
Automatic parallel code generation
Interprocedural dependence analysis
ISSN:0167-8191, 1872-7336
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Shrnutí:The availability of a very accurate dependence graph for a scalar code is the basis for the automatic generation of an efficient parallel implementation. The strategy for this task which is encapsulated in a comprehensive data partitioning code generation algorithm is described. This algorithm involves the data partition, calculation of assignment ranges for partitioned arrays, addition of a comprehensive set of execution control masks, altering loop limits, addition and optimisation of communications for all data. In this context, the development and implementation of strategies to merge communications wherever possible has proved an important feature in producing efficient parallel implementations for numerical mesh based codes. The code generation strategies described here are embedded within the Computer Aided Parallelisation tools (CAPTools) software as a key part of a toolkit for automating as much as possible of the parallelisation process for mesh based numerical codes. The algorithms used enables parallelisation of real computational mechanics codes with only minor user interaction and without any prior manual customisation of the serial code to suit the parallelisation tool.
Bibliografia:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0167-8191
1872-7336
DOI:10.1016/0167-8191(96)00005-1