NAG Library for SMP & Multicore: Performance Examples

The routines in the NAG Library that benefit from SMP parallelism include problem solvers in the areas of: Dense and Sparse Linear Algebra; Fast Fourier Transforms; Random Number Generators; Quadrature; Partial Differential Equations; Interpolation; Curve and Surface Fitting; Correlation and Regression Analysis; Multivariate Methods; Time Series Analysis; Financial Option Pricing; Global Optimization and Wavelet Transforms.

The examples below, illustrate how the performance scales on multiple cores. They are drawn from Library Chapters that cover Sorting, Correlation and Regression Analysis, Wavelet Transforms, Interpolation, Random number generators and Special Functions.


quicksort Algorithm (m01ca) graph

Kendall/Spearman correlation coefficients (g02bn) graph

two dimensional wavelet transform (c09ea) graph

five dimentional interpolation (e01tn) graph

pseudorandom number generator (g05sa) graph

European option pricing formula (s30aa) graph

Note: Whilst a significant number of routines in the NAG Library for SMP and multicore exhibit improved runtime performance, compared to the equivalent routine in the NAG Fortran Library, this is not always the case. To determine the speedup you should consult the document Tuned and Enhanced Routines in the NAG Library for SMP & Multicore and read whether the routine you intend to use benefits, either directly or indirectly, from the use of multiple processors.

Hardware platform for these results:

AMD Opteron 6174 processors. Each processor core is running at 2.2 GHz.