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https://issues.apache.org/jira/browse/SYSTEMML-913?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Matthias Boehm resolved SYSTEMML-913.
-------------------------------------
       Resolution: Fixed
    Fix Version/s: SystemML 0.11

> Performance matrix-vector multiplication w/ tall rhs vector
> -----------------------------------------------------------
>
>                 Key: SYSTEMML-913
>                 URL: https://issues.apache.org/jira/browse/SYSTEMML-913
>             Project: SystemML
>          Issue Type: Task
>            Reporter: Matthias Boehm
>            Assignee: Matthias Boehm
>             Fix For: SystemML 0.11
>
>
> So far, we compute matrix-vector multiplication with simple row-wise dot 
> products. This works very well for the common case of tall&skinny matrices, 
> where the right-hand-side vector is very small. However, for scenarios with 
> many features and hence a tall rhs vector, this approach suffers from cache 
> unfriendly behavior. Accordingly, this task tracks the introduction of a 
> dedicated cache-conscious matrix-vector multiplication for both sparse and 
> dense matrices. 



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