Toward Automatic Data Distribution for Migrating Computations

Program parallelization requires mapping computation and data to processing elements. Navigational programming (NavP), based on the principle of migrating computations, offers a different approach than the conventional solutions that use a SPMD model. This paper focuses on data distribution for NavP...

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Vydáno v:Proceedings of the International Conference on Parallel Processing s. 27
Hlavní autoři: Lei Pan, Jingling Xue, Ming Kin Lai
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.09.2007
Témata:
Computer science
Concurrent computing
data distribution
Distributed computing
graph partitioning
Laboratories
Mobile computing
Navigation
navigational programming
navigational trace graph
NTG
Parallel processing
Pipelines
Propulsion
Yarn
ISSN:0190-3918
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Shrnutí:Program parallelization requires mapping computation and data to processing elements. Navigational programming (NavP), based on the principle of migrating computations, offers a different approach than the conventional solutions that use a SPMD model. This paper focuses on data distribution for NavP. We introduce the navigational trace graph (NTG), a mathematical structure that captures the alignment and distribution preferences of a sequential program. Graph partitioning is applied to NTGs to obtain data distribution solutions. The major advantage is that our methodology can focus exclusively on reducing communication overhead first and later determine the actual computation partition and parallelization, because NavP computations migrate freely across partitions. This is in stark contrast to SPMD, where the data partitioning imposes hard constraints on the threads because they are stationary. We present experimental results to demonstrate the effectiveness of our approach.
ISSN:0190-3918
DOI:10.1109/ICPP.2007.80