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Graphics processing units (GPUs) are powerful tools in data parallel processing but lie idle most of the time. In this study, we propose an approach to improve the performance of vector data rendering by using the parallel computing capability of many\u2010core GPUs. Vertex transformation, largely a mathematical calculation that does not require communication with the host storage device, is a time\u2010consuming procedure because all coordinates of each vector feature need to be transformed to screen vertices. Use of a GPU enables optimization of a general\u2010purpose mathematical calculation, enabling the procedure to be executed in parallel on a many\u2010core GPU and optimized effectively. This study mainly focuses on: (1) an organization and storage strategy for vector data based on equal pitch alignment, which can adapt to the GPU's calculating characteristics; (2) a paging\u2010coalescing transfer and memory access strategy for vector data between the CPU and the GPU; and (3) a balancing allocation strategy to take full advantage of all processing cores of the GPU. Experimental results demonstrate that the approach proposed can significantly improve the efficiency of vector data rendering.<\/jats:p>","DOI":"10.1111\/tgis.12275","type":"journal-article","created":{"date-parts":[[2017,5,25]],"date-time":"2017-05-25T15:57:09Z","timestamp":1495727829000},"page":"1217-1236","update-policy":"http:\/\/dx.doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["An efficient data organization and scheduling strategy for accelerating large vector data rendering"],"prefix":"10.1111","volume":"21","author":[{"given":"Mingqiang","family":"Guo","sequence":"first","affiliation":[{"name":"Faculty of Information &amp; Engineering China University of Geosciences (Wuhan)"},{"name":"Development and Support Department, Wuhan Zondy Cyber Science and Technology Co., Ltd."}]},{"given":"Ying","family":"Huang","sequence":"additional","affiliation":[{"name":"Development and Support Department, Wuhan Zondy Cyber Science and Technology Co., Ltd."}]},{"given":"Qingfeng","family":"Guan","sequence":"additional","affiliation":[{"name":"Faculty of Information &amp; Engineering China University of Geosciences (Wuhan)"},{"name":"National Engineering Research Center of GIS China University of Geosciences (Wuhan)"}]},{"given":"Zhong","family":"Xie","sequence":"additional","affiliation":[{"name":"Faculty of Information &amp; Engineering China University of Geosciences (Wuhan)"},{"name":"National Engineering Research Center of GIS China University of Geosciences (Wuhan)"}]},{"given":"Liang","family":"Wu","sequence":"additional","affiliation":[{"name":"Faculty of Information &amp; Engineering China University of Geosciences (Wuhan)"},{"name":"National Engineering Research Center of GIS China University of Geosciences (Wuhan)"}]}],"member":"311","published-online":{"date-parts":[[2017,5,23]]},"reference":[{"key":"e_1_2_7_2_1","first-page":"298","article-title":"Large\u2010scale vector data visualization using high performance computing","volume":"2","author":"Ali A. 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