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Architecture of an automatically tuned linear algebra library

机译:自动调整的线性代数库的体系结构

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One approach for a hierarchical architecture of a set of linear algebra libraries with self-optimisation capacity is shown. In previous works the optimisation of several routines was studied separately, and in this work the ideas applied to individual routines are combined with the classical hierarchy of linear algebra libraries. Each self-optimised library consists of the former routines of the library and additional special routines which obtain information of the characteristics on the system and tune certain parameters of the former routines accordingly. The relationship between libraries of the different levels of the hierarchy is also strengthened. Just as each routine has in its code different calls to lower levels, so this routine will use the self-optimisation information of these other routines to generate its own information. Experiments with routines of different levels and on different kinds of platforms with constant, variable and heterogeneous load have been carried out. The results obtained allow us to conclude that the proposed methodology is valid for obtaining self-optimised linear algebra libraries.
机译:显示了一种具有自优化能力的一组线性代数库的分层体系结构的方法。在以前的工作中,单独研究了几种例程的优化,并且在这项工作中,将应用于单个例程的思想与线性代数库的经典层次结构相结合。每个自我优化的库都由该库的以前的例程和其他特殊例程组成,这些例程会获取系统特性的信息并相应地调整以前的例程的某些参数。层次结构不同级别的库之间的关系也得到了加强。就像每个例程在其代码中对较低级别的调用不同,该例程将使用其他例程的自优化信息来生成自己的信息。在不同级别,具有恒定,可变和异构负载的平台上使用不同级别的例程进行了实验。获得的结果使我们得出结论,即所提出的方法对于获得自优化的线性代数库是有效的。

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