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From "Jerome (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (SPARK-8514) LU factorization on BlockMatrix
Date Wed, 02 Sep 2015 05:19:45 GMT

     [ https://issues.apache.org/jira/browse/SPARK-8514?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Jerome updated SPARK-8514:
--------------------------
    Attachment: Matrix Factorization - M...ark 1.5.0 Documentation.pdf

I added a version of the Documentation that contains some of the design documentation for
the LU algorithm.  Some of the descriptions may not be necessary for Spark users, but could
be useful for reviewers.  Cheers, Jerome

> LU factorization on BlockMatrix
> -------------------------------
>
>                 Key: SPARK-8514
>                 URL: https://issues.apache.org/jira/browse/SPARK-8514
>             Project: Spark
>          Issue Type: New Feature
>          Components: MLlib
>            Reporter: Xiangrui Meng
>              Labels: advanced
>         Attachments: BlockMatrixSolver.pdf, BlockPartitionMethods.py, BlockPartitionMethods.scala,
LUBlockDecompositionBasic.pdf, Matrix Factorization - M...ark 1.5.0 Documentation.pdf, testScript.scala
>
>
> LU is the most common method to solve a general linear system or inverse a general matrix.
A distributed version could in implemented block-wise with pipelining. A reference implementation
is provided in ScaLAPACK:
> http://netlib.org/scalapack/slug/node178.html



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