计算机工程2016，Vol.42Issue(12)：44-49,6.DOI:10.3969/j.issn.1000-3428.2016.12.009
NVIDIA Tegra K1异构计算平台访存优化研究
Research on Memory Access Optimization of NVIDIA Tegra K1 Heterogeneous Computing Platform
摘要
Abstract
During the transplantation and optimization of the heterogeneous computing platform,memory access performance of digital image data algorithm becomes the main factor.In order to solve the problem,this paper combines with the NVIDIA Tegra K1 hardware architecture's characteristics and the specific algorithm's characteristics,reserches the implementation and memory access performance optimization of matrix transpose and Laplace filtering algorithms on the NVIDIA Tegra K1 heterogeneous computing platform from memory access optimization of consolidation and vectorization,eliminating global memory access's bank and channel conflict etc.Experimental result shows that the performance of matrix transpose and Laplace filtering algorithms on the NVIDIA Tegra K1 heterogeneous computing platform has an obvious improvement,and has good real-time performance.关键词
GPU优化/访存带宽/数据本地化/向量化/合并访问/拉普拉斯滤波算法Key words
GPU optimization/memory access bandwidth/data localization/vectorization/coalesced access/Laplace filtering algorithm分类
信息技术与安全科学引用本文复制引用
梁军,李威,肖琳,徐歆恺..NVIDIA Tegra K1异构计算平台访存优化研究[J].计算机工程,2016,42(12):44-49,6.基金项目
国家自然科学基金重大研究计划项目(91420202) （91420202）
北京市教育委员会科技计划面上项目(SQKM201411417010,KM2015 11417003). （SQKM201411417010,KM2015 11417003）
