Hi, will. The main points of using this code the following:

1.Input data are three one-dimensional arrays - X - arguments of interpolated function, Y - values of this function, XX - points in which spline should be calculated;

2. Dimensions of this arrays (X, Y) are expected quite big up to 200-300 thousand knots therefore problem of algorithm's performance is critical (the code from Koders processing 50 000 knots about 45 000 000 "units of time" (i don't know exactly what is this :) are measured by QueryPerformanceCounter whereas some other code (for example this one http://forum.sources.ru/index.php?showtopic=9853 ) does this job (but incorrect :) 500 times faster(!));

3. I do need to calculate spline for 3 knots too (and 2 - minimum) (Koders produce an error in this case);

4. Boundary conditions are not-a-knot strictly (the result should fully coincide with the matlab's one);

5. Output is an array of the values of cubic spline in points given in XX. Looks like the most impotant things I've described.

Best regards. Sergey