Xeon Phi平台上基于模板优化的3D GVF场计算加速.

3DGradient Vector Flow(GVF)field has wide applications in many image processing algorithms. The computation of GVF field typically needs several iterations and is rather time consuming. Therefore, it is important and meaningful to improve the computation speed of 3DGVF field. The data level parallelism and thread level parallelism are introduced to accelerate the GVF field computation procedure on Intel Xeon Phi many core integrated platform for the first time. Meanwhile, GVF field computation is a kind of stencil computation, whose computation-memory access ratio is low. A novel cache blocking strategy is proposed to fully utilize the L2 cache of Xeon Phi architecture, and to improve the computation speed of GVF field. The experimental results show that the proposed optimizations could effectively improve the speed of GVF filed computation. Especially, for a 512³ 3Dimage, compared with the performance obtained by a 2. 6GHz 8core 16 threads Intel Xeon E5-2670 CPU, the speedup achieved on Xeon Phi is 2. 77 X. [ABSTRACT FROM AUTHOR]