[
https://issues.apache.org/jira/browse/MAHOUT6?page=com.atlassian.jira.plugin.system.issuetabpanels:commenttabpanel&focusedCommentId=12577037#action_12577037 ]
Dawid Weiss commented on MAHOUT6:

A quickie:
1. Make many, many rounds through the same code and throw away initial observations. JVMs tend to optimize code after some time (and compile it to native code of course). A single run is definitely not enough.
2. There is no HashMap on primitive types in the JDK. It's done on boxed types  while these yield to lowlevel optimizations, I doubt you'll get much improvement.
> Need a matrix implementation
> 
>
> Key: MAHOUT6
> URL:
https://issues.apache.org/jira/browse/MAHOUT6> Project: Mahout
> Issue Type: New Feature
> Reporter: Ted Dunning
> Assignee: Grant Ingersoll
> Attachments: MAHOUT6a.diff, MAHOUT6b.diff, MAHOUT6c.diff, MAHOUT6d.diff, MAHOUT6e.diff, MAHOUT6f.diff, MAHOUT6g.diff, MAHOUT6h.patch, MAHOUT6i.diff, MAHOUT6j.diff, MAHOUT6k.diff, MAHOUT6l.patch
>
>
> We need matrices for Mahout.
> An initial set of basic requirements includes:
> a) sparse and dense support are required
> b) row and column labels are important
> c) serialization for hadoop use is required
> d) reasonable floating point performance is required, but awesome FP is not
> e) the API should be simple enough to understand
> f) it should be easy to carve out submatrices for sending to different reducers
> g) a reasonable set of matrix operations should be supported, these should eventually include:
> simple matrixmatrix and matrixvector and matrixscalar linear algebra operations, A B, A + B, A v, A + x, v + x, u + v, dot(u, v)
> row and column sums
> generalized level 2 and 3 BLAS primitives, alpha A B + beta C and A u + beta v
> h) easy and efficient iteration constructs, especially for sparse matrices
> i) easy to extend with new implementations

This message is automatically generated by JIRA.

You can reply to this email to add a comment to the issue online.