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https://issues.apache.org/jira/browse/SPARK-8514?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14614498#comment-14614498
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Qian Huang commented on SPARK-8514:
-----------------------------------
LU factorization is implemented in parallel with a communication pipeline model
based on MPI in scalapack. In MLlib, a similar algorithm can be implemented
with a pipeline model based on synchronizated shuffle, together with using
breeze. I've some experience in Scalapack, and would like to start work on this
issue. I am a starter of MLlib and only work on SparkR for some time though.
> 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
>
> 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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