You are viewing a plain text version of this content. The canonical link for it is here.

Posted to issues@systemml.apache.org by "Matthias Boehm (JIRA)" <ji...@apache.org> on 2017/07/20 08:07:00 UTC

[jira] [Created] (SYSTEMML-1792) Performance issue sparse-dense matrix multiply

Matthias Boehm created SYSTEMML-1792:
----------------------------------------

             Summary: Performance issue sparse-dense matrix multiply
                 Key: SYSTEMML-1792
                 URL: https://issues.apache.org/jira/browse/SYSTEMML-1792
             Project: SystemML
          Issue Type: Bug
            Reporter: Matthias Boehm


Our sparse-dense matrix multiply is already cache conscious but used very small block static block sizes, which were optimized for moderate sparsity. However, for cases with very sparse matrices (and skinny right hand size matrices), the small block sizes add substantial overhead of more than an order of magnitude. This task aims to make these block sizes adaptive, consistent with our cache-conscious implementations of sparsity exploiting matrix multiply operators such as wsloss.



--
This message was sent by Atlassian JIRA
(v6.4.14#64029)