Hardware accelerators for information retrieval and data mining
Valery Sklyarov, Iouliia Skliarova, João P. Silva, Alexander Sudnitson, Artjom Rjabov · 2015
Many algorithms in informatics require a set of objects with similar properties to be grouped (clustered) on the basis of some predefined criteria. The proposed technique involves hierarchical merging in which software, responsible for solving the entire problem, is enhanced with highly parallel networks in hardware accelerators. Additional improvements are achieved with the aid of support methods that are sort and verification of object intersections that may also be autonomously used for other types of information processing and database management. It is shown and experimentally proved that the proposed solutions are efficient. They can be used in such areas as health care, statistical data manipulation and so on.