mxnet-dev mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "Chris Olivier (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (MXNET-4) Performance: Refactor Random and ParallelRandom resources to use MKL for MKL builds
Date Tue, 16 Jan 2018 19:41:00 GMT

     [ https://issues.apache.org/jira/browse/MXNET-4?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Chris Olivier updated MXNET-4:
------------------------------
    Labels: performance  (was: )

> Performance: Refactor Random and ParallelRandom resources to use MKL for MKL builds
> -----------------------------------------------------------------------------------
>
>                 Key: MXNET-4
>                 URL: https://issues.apache.org/jira/browse/MXNET-4
>             Project: Apache MXNet
>          Issue Type: Improvement
>            Reporter: Chris Olivier
>            Priority: Major
>              Labels: mkl, performance
>
> Refactor Random and ParallelRandom resources to use MKL for MKL builds
> Things such as RngUniform, etc.  Similarly to what is done for dropout operator.
> It may need to allocate some temporary memory and generate random numbers in batches,
then serving them out from that batch. 
> Also the Random classes could export a "fill buffer with randoms" function, which seems
to be a common use-case and fits the MKL API more closely.
> Care must be taken regarding MKL's fixed output types for some of the API functions.



--
This message was sent by Atlassian JIRA
(v7.6.3#76005)

Mime
View raw message