报告题目：GPU CUDA-based parallel algorithm design and implementation, applied for computer vision / optimization problems in 2D/3D Euclidean space
报告华体会网页版登陆入口：2019年5月16日上午10：30
报告地点：校本部计算机楼308会议室
报告人：乔文豹博士
摘要：Parallelism working on GPU CUDA platform is one of the most economical ways to hugely accelerate performance of an originally high time complexity algorithm. Through redesign an algorithm, make it adapted to the characteristic of CUDA platform, a very classic algorithm, for example the 2-opt that takes O(n*n) time complexity, can now work in O(n) time complexity using our algorithm.
Also, many world-class companies and universities, like Apple, Dassault, Huawei, UCL, have met the same problem of too much running time when they use their existing sequential computer vision algorithms, like an existing sequential stereo matching or optical flow algorithm. So, they are also seeking for acceleration based on GPU CUDA for applications in both 2D and 3D Euclidean space. Our latest PhD research has success result on K-D Euclidean applications.
During the procedure of re-design an existing algorithm or design totally new algorithm for a concrete application, many new algorithms will be found and explored.
个人摘要：Dr. Qiao got his PhD degree sponsored by CSC and assigned by the engineering University of Technology of Belfort-Montbéliard in France. After graduated on September 2018, he was recruited as a technique consultant by the world top 10 university, UCL, in London United Kingdom. His research topics relate to GPU CUDA parallelism for applications in 2D/3D Euclidean space, applied for accelerating computer vision、optimization problems that is NP hard.
学术兼职：无
