Multithreading with separate data to improve the performance of Backpropagation method
Mulia Dhamma, Muhammad Zarlis, Erna Budhiarti Nababan · Journal of Physics Conference Series · 2017
Backpropagation is one method of artificial neural network that can make a prediction for a new data with learning by supervised of the past data. The learning process of backpropagation method will become slow if we give too much data for backpropagation method to learn the data. Multithreading with a separate data inside of each thread are being used in order to improve the performance of backpropagtion method . Base on the research for 39 data and also 5 times experiment with separate data into 2 thread, the result showed that the average epoch become 6490 when using 2 thread and 453049 epoch when using only 1 thread. The most lowest epoch for 2 thread is 1295 and 1 thread is 356116. The process of improvement is caused by the minimum error from 2 thread that has been compared to take the weight and bias value. This process will be repeat as long as the backpropagation do learning.