[ https://issues.apache.org/jira/browse/IGNITE-5278?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16028435#comment-16028435 ]
Artem Malykh commented on IGNITE-5278: -------------------------------------- We have some problems here: the natural approach for this task is to delegate BLAS calls to any of existing BLAS libs. All BLAS libraries which I met during implementing this task (jBlas, netlib-java) require storing internal data for matrices flattened (i.e [row1, row2...rown] instead of [[row1], [row2], ... [rowN]]), therefore it seems that we have two options here: 1. Redesign storing; 2. keep storing, but do flatten array -> do blas call -> unflatten underlying arrays. If we take second approach, we do not get any boost (rather, we'll get slowdowns) in BLAS levels 1 and 2 for array based matrix impls. We still can get boost in BLAS level 3 calls. For first approach to be taken, separate research task need to be done. > BLAS implementation > ------------------- > > Key: IGNITE-5278 > URL: https://issues.apache.org/jira/browse/IGNITE-5278 > Project: Ignite > Issue Type: Sub-task > Components: ml > Reporter: Yury Babak > Assignee: Artem Malykh > Fix For: 2.1 > > > We need BLAS implementation for local computations. -- This message was sent by Atlassian JIRA (v6.3.15#6346)