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The infinity Lambda test; A multi-dimensional version of Banerjee infinity test

机译:无限Lambda测试;多维版本的Banerjee无限大测试

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摘要

The Banerjee infinity test accurately determines data dependence for one linear equation under symbolic limits and any given direction vectors (U. Banerjee, Depence Analysis for Supercomputing, Kluwer Academic Publishers, Norwell, MA, 1988, P.M. Petersen, Evalua- tion of programs and parallelizing compilers using dynamic analysis techniques, Ph.D. Thesis, University of Illinois at Urbana--Champaign, January 1993). For m linear equations with the same constraints, as each linear equation has to be tested separately, the Banerjee infinity test may generally lose the accuracy. In this paper, we proposed the infinity Lambda test -- a multi- dimensional version of the Banerjee infinity test. The infinity Lambda test can be applied to deal with data dependence of coupled arrays with symbolic (unknown at compile time) bounds. Experiments with benchmark showed that the infinity Lambda test increases the success rate of the Lambda test by approximately 12/100.
机译:Banerjee无穷大测试可准确确定一个线性方程在符号限制和任何给定方向向量下的数据依赖性(U. Banerjee,超级计算的Depence分析,Kluwer Academic Publishers,Norwell,MA,1988,PM Petersen,程序评估和并行化)使用动态分析技术的编译器,伊利诺伊大学香槟分校的博士学位论文,1993年1月)。对于具有相同约束的m个线性方程,由于每个线性方程都必须分别进行测试,因此Banerjee无穷大测试通常可能会失去精度。在本文中,我们提出了无限Lambda测试-Banerjee无限测试的多维版本。无限Lambda测试可用于处理具有符号(编译时未知)边界的耦合数组的数据依赖性。使用基准进行的实验表明,无穷大Lambda测试将Lambda测试的成功率提高了大约12/100。

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