Parallelization of large scale data clustering analytics

A computer-implemented method, comprising:

• determining a plurality of samples stored in a database with associated attributes;
• determining a plurality of sample clusters;
• reproducing the plurality of sample clusters for processing by a plurality of processing cores, wherein each of the reproduced plurality of sample clusters is stored for processing by a corresponding group of at least two of the plurality of processing cores;
• dividing the plurality of samples into a number of sample subsets corresponding to a number of the corresponding groups of the plurality of processing cores;
• associating each of the number of sample subsets with a corresponding group of the plurality of processing cores;
• performing a comparison of each sample of each sample subset with respect to each of the plurality of sample clusters reproduced at the corresponding group, based on associated attributes thereof, and
• dividing, for each sample subset, attributes associated with each sample thereof into attribute subsets for parallel processing thereof during the performing of the comparison and using the at least two of the plurality of processing cores of the corresponding group.

A computer program product, the computer program product being tangibly embodied on a non-transitory computer-readable medium and comprising instructions that, when executed, are configured to:

• determine a plurality of samples stored in a database with associated attributes;
• determine a plurality of sample clusters;
• reproduce the plurality of sample clusters for processing by a plurality of processing cores, wherein each of the reproduced plurality of sample clusters is stored for processing by a corresponding group of at least two of the plurality of processing cores;
• divide the plurality of samples into a number of sample subsets corresponding to a number of the corresponding groups of the plurality of processing cores;
• associate each of the number of sample subsets with a corresponding group of the plurality of processing cores;
• perform a comparison of each sample of each sample subset with respect to each of the plurality of sample clusters reproduced at the corresponding group, based on associated attributes thereof, and
• divide, for each sample subset, attributes associated with each sample thereof into attribute subsets for parallel processing thereof during the performing of the comparison and using the at least two of the plurality of processing cores of the corresponding group.