Data Dependence Analysis Techniques for Increased Accuracy and Extracted Parallelism

@article{Kyriakopoulos2004DataDA,
  title={Data Dependence Analysis Techniques for Increased Accuracy and Extracted Parallelism},
  author={Konstantinos Kyriakopoulos and Kleanthis Psarris},
  journal={International Journal of Parallel Programming},
  year={2004},
  volume={32},
  pages={317-359}
}
Parallelizing compilers rely on data dependence information in order to produce valide parallel code. Traditional data dependence analysis techniques, such as the Banerjee test and the I-Test, can efficiently compute data dependence information for simple instances of the data dependence problem. However, in more complex cases involving triangular or trapezoidal loop regions, symbolic variables, and multidimensional arrays with coupled subscripts these tests, including the triangular Banerjee… CONTINUE READING
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A general data dependence analysis to nested loop using integer interval theory

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