[jira] Commented: (MAHOUT-6) Need a matrix implementation

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[jira] Commented: (MAHOUT-6) Need a matrix implementation

Tim Allison (Jira)

    [ https://issues.apache.org/jira/browse/MAHOUT-6?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12576381#action_12576381 ]

Jason Rennie commented on MAHOUT-6:

Btw, noticed the matrix stuff is currently under utils.matrix and utils.vector.  The matrix package is so important that I'd think we'd want it to have it's own package (org.apache.mahout.matrix).  Also, we should not separate vector/matrix classes into separate packages b/c matrix-vector products will likely need to access protected members of both classes for efficient operation.  Ted, Jeff, do you agree, or am I missing something here?

> Need a matrix implementation
> ----------------------------
>                 Key: MAHOUT-6
>                 URL: https://issues.apache.org/jira/browse/MAHOUT-6
>             Project: Mahout
>          Issue Type: New Feature
>            Reporter: Ted Dunning
>         Attachments: MAHOUT-6a.diff, MAHOUT-6b.diff, MAHOUT-6c.diff, MAHOUT-6d.diff, MAHOUT-6e.diff, MAHOUT-6f.diff, MAHOUT-6g.diff, MAHOUT-6h.patch, MAHOUT-6i.diff, MAHOUT-6j.diff
> 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 sub-matrices for sending to different reducers
> g) a reasonable set of matrix operations should be supported, these should eventually include:
>     simple matrix-matrix and matrix-vector and matrix-scalar 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

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