Parallel algorithm for reduction of data processing time in big data
Date
2020
2020
Author
Silva, Jesús
Hernandez Palma, Hugo Gaspar
Niebles Núñez, William
Ovallos-Gazabon, David
Varela, Noel
Metadata
Show full item record
Show full item record
Abstract
Technological advances have allowed to collect and store large volumes of data over the years. Besides, it is significant that today's applications have high performance and can analyze these large datasets effectively. Today, it remains a challenge for data mining to make its algorithms and applications equally efficient in the need of increasing data size and dimensionality [1]. To achieve this goal, many applications rely on parallelism, because it is an area that allows the reduction of cost depending on the execution time of the algorithms because it takes advantage of the characteristics of current computer architectures to run several processes concurrently [2]. This paper proposes a parallel version of the FuzzyPred algorithm based on the amount of data that can be processed within each of the processing threads, synchronously and independently.
Collections