Abstract:
Frequent pattern mining is a discipline with many
practical applications, where massive computational power
and speed are required. Many state-of-the-art frequent
pattern mining applications have inefficient solutions for
both shared memory and multiprocessor systems due to
problems with parallelism and memory. One of possible
solutions to the trouble is the use of Graphics Processing
Unit (GPU) in the organization along with modification of
classical mining algorithms in such a manner, that the
sequential part of the algorithm is run on the server and the
parallel port on GPU.s. Here we present a survey of multi core and GPU accelerated parallelization of the FIM
algorithms
