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Posted to issues@systemml.apache.org by "Matthias Boehm (JIRA)" <ji...@apache.org> on 2016/09/13 17:21:20 UTC

[jira] [Created] (SYSTEMML-913) Performance matrix-vector multiplication w/ tall rhs vector

Matthias Boehm created SYSTEMML-913:
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             Summary: 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


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. This tasks tracks the dedicated handling of cache-conscious matrix-vector multiplication for both sparse and dense matrices. 



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