In this research, we show effect of auto-tuning (AT) for function of code selection to computational kernels for scientific and technology computations. ppOpen-AT, which is a computer language to specify AT function to arbitrary parts of program, is utilized to describe the code selection. The evaluation of AT in this research performed with advanced CPU architectures, such as the Intel Xeon Phi and the Intel Ivy Bridge. Results of preliminary experiment with a code based on Finite Difference Method (FDM) indicate that the effect of AT is crucial with compared to conventional AT framework without code selection.