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From "DB Tsai (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-17134) Use level 2 BLAS operations in LogisticAggregator
Date Fri, 23 Sep 2016 05:49:20 GMT

    [ https://issues.apache.org/jira/browse/SPARK-17134?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15515491#comment-15515491
] 

DB Tsai commented on SPARK-17134:
---------------------------------

I did benchmark again. In old implementation, it takes 1.3hrs for one iteration, and in new
implementation, it takes 3.5hrs for one iteration. I ran both experiment in the same spark
job for fairness since they will get the same # of executors. I suspect that in old implementation,
we cache the standardized dataset resulting better performance.   

> Use level 2 BLAS operations in LogisticAggregator
> -------------------------------------------------
>
>                 Key: SPARK-17134
>                 URL: https://issues.apache.org/jira/browse/SPARK-17134
>             Project: Spark
>          Issue Type: Sub-task
>          Components: ML
>            Reporter: Seth Hendrickson
>
> Multinomial logistic regression uses LogisticAggregator class for gradient updates. We
should look into refactoring MLOR to use level 2 BLAS operations for the updates. Performance
testing should be done to show improvements.



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