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Posted to issues@systemml.apache.org by "Matthias Boehm (JIRA)" <ji...@apache.org> on 2017/12/09 01:36:00 UTC

[jira] [Closed] (SYSTEMML-2039) Memory-inefficiency due to breadth-first instruction generation

     [ https://issues.apache.org/jira/browse/SYSTEMML-2039?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Matthias Boehm closed SYSTEMML-2039.
------------------------------------
       Resolution: Fixed
         Assignee: Matthias Boehm
    Fix Version/s: SystemML 1.0

> Memory-inefficiency due to breadth-first instruction generation 
> ----------------------------------------------------------------
>
>                 Key: SYSTEMML-2039
>                 URL: https://issues.apache.org/jira/browse/SYSTEMML-2039
>             Project: SystemML
>          Issue Type: Bug
>            Reporter: Matthias Boehm
>            Assignee: Matthias Boehm
>             Fix For: SystemML 1.0
>
>
> In large DAGs, the strict topological ordering (breadth-first) instruction generation causes unnecessary memory-inefficiency and unnecessary evictions. Depth-first instruction generation ensures that all consumers of a DAG input (bound to a logical variable name) are executed before the logical variable is overwritten by an output. For example, in below script
> {code}
> E = A * B + C * D
> F = (A + B) + (C + D)
> {code}
> we compute A*B, C*D, A+B, C+D, and subsequently AB+CD, (A+B)+(C+D), which causes unnecessary memory pressure in the lower levels of the DAG. Furthermore, this also causes poor temporal locality.
> Instead, we should use a two-level approach where all intermediates are computed in a depth-first manner, and all transient writes are scheduled after these operations.



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