Knowledge Discovery in Auto-tuning Parallel Numerical Library
Knowledge Discovery in Auto-tuning Parallel Numerical Library
复制标题
自调并行数值库中的知识发现
DOI：
10.1007/3-540-45884-0_48
复制
发表时间：
2002
期刊：
影响因子：
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通讯作者：
Y. Kanada
中科院分区：
文献类型：
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作者：
H. Kuroda;T. Katagiri;Y. Kanada
本文提出了称为ILIB的并行数值库，该库通过可选的计算内核，处理器之间的通信方法以及循环扩展的各个数量的展开来实现自动调整设施。这种自动调整方法不仅在库的可用性中，而且在库的性能方面都具有优势。实际上，绩效评估的结果表明，参数的自动调节或自动纠正功能是获得高性能的关键技术。通过这种自动调整方法自动选择的一组参数为我们提供了几种重要知识，以实现高效的程序生产。总的来说，这类知识将有助于我们制定其他一些高性能计划。
This paper proposes the parallel numerical library called ILIB which realises auto-tuning facilities with selectable calculation kernels, communication methods between processors, and various number of unrolling for loop expansion. This auto-tuning methodology has advantage not only in usability of library but also in performance of library. In fact, results of the performance evaluation show that the auto-tuning or auto-correction feature for the parameters is a crucial technique to attain high performance. A set of parameters which are auto-selected by this auto-tuning methodology gives us several kinds of important knowledge for highly efficient program production. These kinds of knowledge will help us to develop some other high-performance programs, in general.