[
https://issues.apache.org/jira/browse/OPENNLP-703?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14084288#comment-14084288
]
Vinh Khuc commented on OPENNLP-703:
-----------------------------------
QNTrainer now accepts the parameter "Threads" for computing the objective
function (negative log-likelihood) and its gradient in parallel. In my small
experiment, with 4 threads, the training time for CONLL 2000 was reduced from
1,788 seconds down to 952 seconds. The speed-up factor is less than 4 since the
for-loops in QNMinimizer still run in sequential manner.
> Parallel computing the objective function and its gradient for MAXENT_QN
> ------------------------------------------------------------------------
>
> Key: OPENNLP-703
> URL: https://issues.apache.org/jira/browse/OPENNLP-703
> Project: OpenNLP
> Issue Type: Improvement
> Components: Machine Learning
> Affects Versions: tools-1.5.3, maxent-3.0.3
> Reporter: Vinh Khuc
> Assignee: Vinh Khuc
> Fix For: 1.6.0
>
>
> Although the current L-BFGS trainer runs in a sequential manner, Maxent's
> objective function (i.e. the negative log-likelihood function) and its
> gradient can be computed in parallel. This JIRA will focus on improving the
> training time of MAXENT_QN.
--
This message was sent by Atlassian JIRA
(v6.2#6252)
