Coping with data dependencies of multi-dimensional array references

Abstract

This paper presents a new static data dependence analysis approach, Dependence Difference Inequality Test, which can deal with coupled subscripts for multi-dimensional array references for software pipelining techniques for nested loops. The Dependence Difference Inequality Test (DDIT) replaces direction vectors with dependence difference inequalities as constraints to variables in a linear system. The method presented in this paper extends the applicable range of the Generalized Lambda Test and seems to be a practical scheme to analyze data dependence. Experimental results show that the number of data independences checked by the DDIT algorithm is slightly smaller than that manually. It is also shown that our method is better than other traditional data dependence analysis methods without increasing time cost: it increases the success rate of the Generalized Lambda Test by approximately 14.19%. © IFIP International Federation for Information Processing 2005.