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https://issues.apache.org/jira/browse/SPARK-8514?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14717696#comment-14717696
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Jerome edited comment on SPARK-8514 at 8/27/15 11:03 PM:
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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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