An approach for composing a performance optimized computational code is suggested for the latest microprocessors. The concept of the code optimization, termed localization, is maximizing the utilization of the second level cache that is common to all the latest computer systems, and minimizing the access to system main memory. In this study, the localized optimization of the LU-SGS (Lower-Upper Symmetric Gauss-Seidel) code for the solution of fluid dynamic equations was carried out in three different levels and tested for several different microprocessor architectures widely used these days. The test results of localized optimization showed a remarkable performance gain of more than two times faster solution than the baseline algorithm for producing exactly the same solution on the same computer system.