WEKA Multilayer Perceptron with large dataset
That is a lot of attributes.  Moreover, WEKA's default MLP size of the hidden layer is "a", where the following preset sizes are given:


a = (features + classes) / 2
i = features
o = classes 
t = features + classes.


It is expected that the MLP will take longer.  Some things you can try:


use dimensionality reduction such as PCA to reduce the number of features
reduce the number of folds if you are using k-fold cross validation
reduce hidden layer size (which will probably negatively affect accuracy)
use another model such as a SVM, which would be a lot faster


I recommend going through this high level introduction to neural networks.  It is important to gain some intuition about the models you are using and the options you have available before tackling your problem.