Data layout transformation for structure vectorization on SIMD architectures
2015 IEEE/ACIS 16th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)(2015)
摘要
Structure references are commonly-used at the core of applications in a multitude of domains such as image processing, signal processing, especially the scientific and engineering applications. SIMD instruction sets, as SSE, AVX, AltiVec and 3DNow, provide a promising and widely available avenue for enhancing performance on modern processors. However existing memory accessing shackles limit the achieved performance for structure reference on modern SIMD architectures. In this paper, we propose a novel data layout transformation technology that addresses the accessing obstacles, along with a static analysis technique for detecting the legal loops in where this transformation is suitable. And this approach is implemented in the Optimizing Compiler Open64. The experimental results show that the proposed method can translate application with structure access into vectorizable codes, thereby advancing the execution efficiency adequately.
更多查看译文
关键词
structure reference,data layout transformation,vectorization,SIMD
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要