Vectorization using reversible data dependences
Date
1994
Authors
Tang, Peiyi
Gao, Nianshu
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Abstract
Data dependences between statements have long been used for detecting parallelism and converting sequential programs into parallel forms. However, some data dependences can be reversed and the transformed program still produces the same results. In this paper, we revisit vectorization and propose a new vectorization algorithm using reversible data dependences. The new algorithm can generate more or thicker vector statements than traditional algorithm. The techniques presented in this paper can be incorporated in all the existing vectorizing compilers for supercomputers.
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parallelism, vectorization algorithm, supercomputers
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