BOAST: Bringing Optimization through Automatic Source-to-Source Transformations

BOAST: Bringing Optimization through Automatic Source-to-Source Transformations
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BOAST:通过自动源到源转换实现优化

DOI:
10.1109/mcsoc.2013.12
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发表时间:
2013
期刊:
2013 IEEE 7th International Symposium on Embedded Multicore Socs
影响因子:
--
通讯作者:
Vania Marangozova
Vania Marangozova
中科院分区:
--
文献类型:
--
作者:
Johan Cronsioe;B. Videau;Vania Marangozova

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在本文中,我们提出了一个自动源代码转换,该转换优化了循环结构,以便为给定的多核平台找到最佳的性能配置。我们专注于卷积操作员,使用循环展开对其进行优化,并表明我们的方法可以达到高达67%的性能增益。我们的实验是通过在Tibidado高性能和低能消耗机上执行的BIGDFT科学应用程序进行的。
In this paper we present an automatic source-to-source transformation which optimizes loop structures in order to find the best performance configuration for a given multi-core platform. We focus on convolution operators, optimize them using loop unrolling and show that our approach can achieve up to 67% performance gain. Our experiments have been done with the BigDFT scientific application executed on the Tibidado high-performance and low-energy-consumption machine.
DOI: --
发表时间: 2009
期刊: Scientific Reports
影响因子: 4.6
作者:
J. Xu
通讯作者: J. Xu