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Posted to issues@spark.apache.org by "Xiangrui Meng (JIRA)" <ji...@apache.org> on 2014/09/19 07:19:33 UTC
[jira] [Resolved] (SPARK-3418) [MLlib] Additional BLAS and Local
Sparse Matrix support
[ https://issues.apache.org/jira/browse/SPARK-3418?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Xiangrui Meng resolved SPARK-3418.
----------------------------------
Resolution: Fixed
Fix Version/s: 1.2.0
Issue resolved by pull request 2294
[https://github.com/apache/spark/pull/2294]
> [MLlib] Additional BLAS and Local Sparse Matrix support
> -------------------------------------------------------
>
> Key: SPARK-3418
> URL: https://issues.apache.org/jira/browse/SPARK-3418
> Project: Spark
> Issue Type: New Feature
> Components: MLlib
> Reporter: Burak Yavuz
> Assignee: Burak Yavuz
> Fix For: 1.2.0
>
>
> Currently MLlib doesn't have Level-2 and Level-3 BLAS support. For Multi-Model training, adding support for Level-3 BLAS functions is vital.
> In addition, as most real data is sparse, support for Local Sparse Matrices will also be added, as supporting sparse matrices will save a lot of memory and will lead to better performance. The ability to left multiply a dense matrix with a sparse matrix, i.e. `C := alpha * A * B + beta * C` where `A` is a sparse matrix will also be added. However, `B` and `C` will remain as Dense Matrices for now.
> I will post performance comparisons with other libraries that support sparse matrices such as Breeze and Matrix-toolkits-JAVA (MTJ) in the comments.
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