Starting from the set of preprocessed SMILES strings X (containing 102, 377, 734 SMILES strings), we constructed a data set D = {(s, t) | s, t ∈ P, κ(s, t) ≥ 0.5} containing all the pairs having a Tanimoto similarity κ(s, t) ≥ 0.50. The Tanimoto similarity is calculated with the RDKit (version 2022.09.5) Morgan binary fingerprint (ECFP4) with radius equals to 2, 1024 bits, calculated from the SMILES strings in X . The number of molecular pairs in D is 217, 111, 386, 586, which is only 0.002% of the over 10 16 possible molecular pairs). The Tanimoto similarity for the molecular pairs can be computed efficiently by storing the fingerprints in a binary matrix of size N × 128 bytes in the GPU memory. In this way, the Tanimoto similarity among all the possible pairs can be efficiently computed by utilizing GPU parallelism. For each SMILES string in X we can calculate the Tanimoto similarity at once against all the other SMILES strings. The calculation of all molecular pairs took 10 days on 16 A100 GPUs with 40GB of memory.