Parallelization of enumerating tree-like chemical compounds by breadth-first search order

Enumeration of chemical compounds greatly assists designing and finding new drugs, and determining chemical structures from mass spectrometry. In our previous study, we developed efficient algorithms, BfsSimEnum and BfsMulEnum for enumerating tree-like chemical compounds without and with multiple bonds, respectively. For many instances, our previously proposed algorithms were able to enumerate chemical structures faster than other existing methods. Latest processors consist of multiple processing cores, and are able to execute many tasks at the same time. In this paper, we develop three parallelized algorithms BfsEnumP1-3 by modifying BfsSimEnum in simple manners to further reduce execution time. BfsSimEnum constructs a family tree in which each vertex denotes a molecular tree. BfsEnumP1-3 divide a set of vertices with some given depth of the family tree into several subsets, each of which is assigned to each processor. For evaluation, we perform experiments for several instances with varying the division depth and the number of processors, and show that BfsEnumP1-3 are useful to reduce the execution time for enumeration of tree-like chemical compounds. In addition, we show that BfsEnumP3 achieves more than 80% parallelization efficiency using up to 11 processors, and reduce the execution time using 12 processors to about 1/10 of that by BfsSimEnum.