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From "Jerome (JIRA)" <j...@apache.org>
Subject [jira] [Comment Edited] (SPARK-8514) LU factorization on BlockMatrix
Date Thu, 27 Aug 2015 23:04:45 GMT

    [ https://issues.apache.org/jira/browse/SPARK-8514?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14717696#comment-14717696
] 

Jerome edited comment on SPARK-8514 at 8/27/15 11:03 PM:
---------------------------------------------------------

I have a draft of the LU Decomposition in BlockMatrix.scala

https://github.com/nilmeier/spark/tree/SPARK-8514_LU_factorization
https://github.com/nilmeier/spark/tree/SPARK-8514_LU_factorization/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/BlockMatrix.scala

Only one unit test so far:
https://github.com/nilmeier/spark/tree/SPARK-8514_LU_factorization/mllib/src/test/scala/org/apache/spark/mllib/linalg/distributed/BlockMatrixSuite.scala

The method here is slightly different than the previously proposed method in that it preforms
large block matrices for large BlockMatrix.multiply operations.  I'll be adding documentation
shortly to github to describe the method.

Cheers, J


was (Author: nilmeier):
I have a draft of the LU Decomposition in BlockMatrix.scala

https://github.com/nilmeier/spark/blob/SPARK-8514_LU_factorization
https://github.com/nilmeier/spark/blob/SPARK-8514_LU_factorization/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/BlockMatrix.scala

Only one unit test so far:
https://github.com/nilmeier/spark/blob/SPARK-8514_LU_factorization/mllib/src/test/scala/org/apache/spark/mllib/linalg/distributed/BlockMatrixSuite.scala

The method here is slightly different than the previously proposed method in that it preforms
large block matrices for large BlockMatrix.multiply operations.  I'll be adding documentation
shortly to github to describe the method.

Cheers, J

> 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, 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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