# HG changeset patch # User Razvan Pascanu # Date 1284469276 14400 # Node ID 29b48deb6a84e90f898cb18b9ef38f0110493c8e # Parent c5c7ba805a2f3173829ee2bfe2064d42e9be2e26 reply/comment regarding the GPU and datasets diff -r c5c7ba805a2f -r 29b48deb6a84 doc/v2_planning/dataset.txt --- a/doc/v2_planning/dataset.txt Mon Sep 13 23:55:04 2010 -0400 +++ b/doc/v2_planning/dataset.txt Tue Sep 14 09:01:16 2010 -0400 @@ -343,3 +343,17 @@ shared variable? Why wouldn't the learner just create this shared variable internally and copy into it the data provided by the dataset? +RP replies: Sure, the learner could take care of all this. Note though that the +learner should take care to divide the dataset into chunks that fit in the +GPU memory ( in case of a large dataset) and then take care of updating the +shared variables acording to the current chunk. Personally I feel like all +this data division, management and so on should be done by the dataset. +It feels more natural that way. For example assume you have a dataset that +is composed of a time series and some static data ( carre-tech heart beat +data is a good example). The static data is small enough so that you could +always store on the GPU, and you would only need to split the time series. +For the learner to do this ( since it gets the same interface from any +dataset object) would be like and if then, while for the +dataset is just a different class. But I'm happy to have all this GPU stuff +send to the learner as well if everybody else believe that is better. +