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https://issues.apache.org/jira/browse/MAHOUT-6?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12577037#action_12577037
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Dawid Weiss commented on MAHOUT-6:
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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 low-level optimizations, I doubt you'll get much
improvement.
> 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
> Assignee: Grant Ingersoll
> 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, MAHOUT-6k.diff,
> MAHOUT-6l.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 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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