[ https://issues.apache.org/jira/browse/SYSTEMML-913?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Matthias Boehm reassigned SYSTEMML-913: --------------------------------------- Assignee: Matthias Boehm > 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. -- This message was sent by Atlassian JIRA (v6.3.4#6332)