[xsl] Performance of XSLT in a neural network application

Hi Folks,

I used XSLT to implement a neural network that recognizes handwritten digits.

I have a small training and test data set consisting of 100 and 10 records, 
respectively.

I also have a large training and test data set consisting of 60,000 and 10,000 
records, respectively

Neural networks involve a lot of matrix operations.

In my first implementation I stored the data in XML and the matrix operations 
operated on XML.

In my second implementation I removed all XML and exclusively used XSLT maps 
and XSLT sequences.

In my third implementation I used Python instead of XSLT.

Here are the performance results:
---------------------------------------------------------------------------------------
For the small training and test data set:

First implementation (XML): 6 and one-half minutes

Second implementation (maps, sequences): 28.7 seconds

Python implementation: less than 1 second
---------------------------------------------------------------------------------------
For the large training and test data set:

First implementation (XML): more than 24 hours (I stopped it after it had run 
for 24 hours)

Second implementation (maps, sequences): 5 hours

Python implementation: 30 seconds
---------------------------------------------------------------------------------------
Conclusion: XSLT is not a viable language for creating neural networks. 

/Roger
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