AIMSim implements many functionalities and can generate similarity density distributions and pairwise heatmaps simply using a list of SMILES strings. One can use the forty-plus distance metrics and common molecular fingerprints, including the Morgan and RDKit specifications . Dimensionality reduction can be performed to visualize high dimensional fingerprints in 2 dimensions. At the implementation level, multithreading and configurable output levels facilitate the analysis of large datasets, as discussed at length in the Case Study #3 (S2). The rest of this section is an overview of the various capabilities of AIMSim.