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From "Janardhan (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (SYSTEMML-1140) Sparse/Caching performance bugs related to deep learning scripts
Date Sat, 24 Feb 2018 04:43:00 GMT

     [ https://issues.apache.org/jira/browse/SYSTEMML-1140?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Janardhan updated SYSTEMML-1140:
--------------------------------
    Affects Version/s: SystemML 1.1

> Sparse/Caching performance bugs related to deep learning scripts
> ----------------------------------------------------------------
>
>                 Key: SYSTEMML-1140
>                 URL: https://issues.apache.org/jira/browse/SYSTEMML-1140
>             Project: SystemML
>          Issue Type: Bug
>    Affects Versions: SystemML 1.0.0, SystemML 1.1
>            Reporter: Niketan Pansare
>            Priority: Blocker
>
> We have identified two performance bugs that frequently occurs in deep learning script.
> First, we repeatedly perform unnecessary conversion to sparse format. Also, the operations
such as matrix multiplication (including BLAS and CuBLAS) are  optimized for dense.
> 	
> Second, even with large memory budget, we sometimes spend almost 20-30% time in caching.
> [~mboehm7] [~reinwald] [~mwdusenb@us.ibm.com] I am labeling this bug as blocker for SystemML
1.0. Please feel free to assign this issue to yourself.



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