Impact of different software implementations on the performance of the Maxmin method for diverse subset selection.

Besides the choice of an automated software method for selecting 'maximally diverse' compounds from a large pool of molecules, it is the implementation of the algorithm that critically determines the usefulness of the approach. The speed of execution of two implementations of the Maxmin algorithm is compared for the selection of maximally diverse subsets of large compound collections. Different versions of the software are compared using various C compiler options and Java virtual machines. The analysis shows that the Maxmin algorithm can be implemented in both languages yielding sufficient speed of execution. For large compound libraries the Java version outperformes the C version. While the Java version selects the same compounds independent of the virtual machine used, the C version produces slightly different subsets depending on the compiler and on the optimization settings.