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From "Matthias Boehm (JIRA)" <j...@apache.org>
Subject [jira] [Resolved] (SYSTEMML-1879) Parfor remote spark w/ reuse of shared inputs
Date Sat, 02 Sep 2017 23:34:00 GMT

     [ https://issues.apache.org/jira/browse/SYSTEMML-1879?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Matthias Boehm resolved SYSTEMML-1879.
--------------------------------------
    Resolution: Done
      Assignee: Matthias Boehm

> Parfor remote spark w/ reuse of shared inputs
> ---------------------------------------------
>
>                 Key: SYSTEMML-1879
>                 URL: https://issues.apache.org/jira/browse/SYSTEMML-1879
>             Project: SystemML
>          Issue Type: Sub-task
>          Components: APIs, Runtime
>            Reporter: Matthias Boehm
>            Assignee: Matthias Boehm
>             Fix For: SystemML 1.0
>
>
> Currently, we read shared inputs redundantly in each parfor worker. This causes redundant
read and is unnecessarily memory-inefficient.
> This task aims to read shared inputs once per process and reuse them across threads.
The most elegant way of handling this is to reuse initially parsed symbol table entries (instances
of matrix objects), except for result variables. Then the sharing happens automatically (similar
to local parfor) over the shared per-process buffer pool. 



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