Re: Podling Report Reminder - July 2017

[Henri Yandell]

Thanks Dominic :)

I signed off with a couple of minor word changes (contributor->committer),
(next->afterwards).

On Wed, Jul 5, 2017 at 9:47 PM, Sebastian  wrote:

> Also signed off!
>
>
>
> On 06.07.2017 00:34, Markus Weimer wrote:
>
>> On Wed, Jul 5, 2017 at 3:30 PM, Suneel Marthi  wrote:
>>
>>> Thanks Dom, the report has been filed.
>>>
>>> Mentors, please sign-off on the report.
>>>
>>
>> Thanks and done!
>>
>> Markus
>>
>>

Re: Podling Report Reminder - July 2017

[Sebastian]

Also signed off!


On 06.07.2017 00:34, Markus Weimer wrote:

On Wed, Jul 5, 2017 at 3:30 PM, Suneel Marthi  wrote:

Thanks Dom, the report has been filed.

Mentors, please sign-off on the report.


Thanks and done!

Markus

Re: Podling Report Reminder - July 2017

[Markus Weimer]

On Wed, Jul 5, 2017 at 3:30 PM, Suneel Marthi  wrote:
> Thanks Dom, the report has been filed.
>
> Mentors, please sign-off on the report.

Thanks and done!

Markus

Re: Podling Report Reminder - July 2017

[Suneel Marthi]

Thanks Dom, the report has been filed.

Mentors, please sign-off on the report.

On Wed, Jul 5, 2017 at 6:10 PM, Dominic Divakaruni <
dominic.divakar...@gmail.com> wrote:

> Please see below. Can one of our mentor's help upload this report to
> https://wiki.apache.org/incubator/July2017
>
> 1. Your project name: Apache MXNet
>
>
>
> 2. A brief description of your project, which assumes no knowledge of
> the project or necessarily of its field
>
> MXNet is an open-source deep learning framework that allows you to define,
> train, and deploy deep neural networks on a wide array of devices, from
> cloud infrastructure to mobile devices. It is highly scalable, allowing for
> fast model training, and supports a flexible programming model and multiple
> languages. MXNet allows you to mix symbolic and imperative programming
> flavors to maximize both efficiency and productivity. MXNet is built on a
> dynamic dependency scheduler that automatically parallelizes both symbolic
> and imperative operations on the fly. A graph optimization layer on top of
> that makes symbolic execution fast and memory efficient. The MXNet library
> is portable and lightweight, and it scales to multiple GPUs and multiple
> machines.
>
>
>
> 3. A list of the three most important issues to address in the move
> towards graduation.
>
> 3.1.  Migrate code (GitHub) and website to Apache.
>
> 3.2.  Grow the community:
>
> 3.2.1. Expand reference material including – new machine learning
> research published based on MXNet, tutorials, documented use cases and
> architecture documentation.
>
> 3.2.2. Improving user-experience –for example improved error messages
>
> 3.2.3. Improved support for various programming languages
>
> 3.2.4. Establish a dependable, Apache-way consistent release process.
>
> 3.3.  Features:
>
> 3.3.1. Capability (such as low precision support and quantization) that
> allows models to run efficiently on mobile and edge devices. Integrations
> with mobile and edge device acceleration drivers.
>
> 3.3.2. Accelerate performance on CPUs and GPUs.
>
>
>
> 4. Any issues that the Incubator PMC or ASF Board might wish/need to be
> aware of: None.
>
>
>
> 5. How has the community developed since the last report.
>
> 5.1.  On 5/27 MXNet published a comprehensive edit and makeover of the
> documentation including tutorials, how-to’s, APIs and architecture guides.
> This was a broad effort that involved over 40 contributors.
>
> 5.2.  The PMC voted in a new contributor who has been helping with the code
> migration and setup of the test infrastructure. We are making slow but
> steady progress towards getting the GitHub code migrated. The target date
> for migration is 7/17. Website migration will happen next.
>
> 5.3.  Slack and dev@ are being used more actively.
>
> 5.4.  Two presentations/workshops on Apache MXNet at the O’Reilly AI Conf
> on 6/27 and 6/28
>
> 5.5.  A new blog post published on 6/23 showing users how to Build a
> Real-time Object Classification System with ApacheMXNet on Raspberry Pi.
> https://aws.amazon.com/blogs/ai/build-a-real-time-object-
> classification-system-with-apache-mxnet-on-raspberry-pi/
>
> 6. How has the project developed since the last report.
>
> 6.1.  Since the last report 42 authors have pushed 326 commits to master.
>
> 6.2.  Documentation- Architecture guides, How To’s, Tutorials, and APIs
> have been improved.
>
> 6.3.  More features (e.g. operators) requested by the user community has
> been added.
>
> 6.4.   A new Perl language binding for MXNet was added.
>
>
>
> 7. How does the podling rate their own maturity. Maturity = Low.
>
>
>
>
>
> On Mon, Jul 3, 2017 at 3:49 AM,  wrote:
>
> > Dear podling,
> >
> > This email was sent by an automated system on behalf of the Apache
> > Incubator PMC. It is an initial reminder to give you plenty of time to
> > prepare your quarterly board report.
> >
> > The board meeting is scheduled for Wed, 19 July 2017, 10:30 am PDT.
> > The report for your podling will form a part of the Incubator PMC
> > report. The Incubator PMC requires your report to be submitted 2 weeks
> > before the board meeting, to allow sufficient time for review and
> > submission (Wed, July 05).
> >
> > Please submit your report with sufficient time to allow the Incubator
> > PMC, and subsequently board members to review and digest. Again, the
> > very latest you should submit your report is 2 weeks prior to the board
> > meeting.
> >
> > Thanks,
> >
> > The Apache Incubator PMC
> >
> > Submitting your Report
> >
> > --
> >
> > Your report should contain the following:
> >
> > *   Your project name
> > *   A brief description of your project, which assumes no knowledge of
> > the project or necessarily of its field
> > *   A list of the three most important issues to address in the move
> > towards graduation.
> > *   Any issues that the Incubator PMC or ASF Board might wish/need 

Re: Podling Report Reminder - July 2017

[Dominic Divakaruni]

Please see below. Can one of our mentor's help upload this report to
https://wiki.apache.org/incubator/July2017

1. Your project name: Apache MXNet



2. A brief description of your project, which assumes no knowledge of
the project or necessarily of its field

MXNet is an open-source deep learning framework that allows you to define,
train, and deploy deep neural networks on a wide array of devices, from
cloud infrastructure to mobile devices. It is highly scalable, allowing for
fast model training, and supports a flexible programming model and multiple
languages. MXNet allows you to mix symbolic and imperative programming
flavors to maximize both efficiency and productivity. MXNet is built on a
dynamic dependency scheduler that automatically parallelizes both symbolic
and imperative operations on the fly. A graph optimization layer on top of
that makes symbolic execution fast and memory efficient. The MXNet library
is portable and lightweight, and it scales to multiple GPUs and multiple
machines.



3. A list of the three most important issues to address in the move
towards graduation.

3.1.  Migrate code (GitHub) and website to Apache.

3.2.  Grow the community:

3.2.1. Expand reference material including – new machine learning
research published based on MXNet, tutorials, documented use cases and
architecture documentation.

3.2.2. Improving user-experience –for example improved error messages

3.2.3. Improved support for various programming languages

3.2.4. Establish a dependable, Apache-way consistent release process.

3.3.  Features:

3.3.1. Capability (such as low precision support and quantization) that
allows models to run efficiently on mobile and edge devices. Integrations
with mobile and edge device acceleration drivers.

3.3.2. Accelerate performance on CPUs and GPUs.



4. Any issues that the Incubator PMC or ASF Board might wish/need to be
aware of: None.



5. How has the community developed since the last report.

5.1.  On 5/27 MXNet published a comprehensive edit and makeover of the
documentation including tutorials, how-to’s, APIs and architecture guides.
This was a broad effort that involved over 40 contributors.

5.2.  The PMC voted in a new contributor who has been helping with the code
migration and setup of the test infrastructure. We are making slow but
steady progress towards getting the GitHub code migrated. The target date
for migration is 7/17. Website migration will happen next.

5.3.  Slack and dev@ are being used more actively.

5.4.  Two presentations/workshops on Apache MXNet at the O’Reilly AI Conf
on 6/27 and 6/28

5.5.  A new blog post published on 6/23 showing users how to Build a
Real-time Object Classification System with ApacheMXNet on Raspberry Pi.
https://aws.amazon.com/blogs/ai/build-a-real-time-object-classification-system-with-apache-mxnet-on-raspberry-pi/

6. How has the project developed since the last report.

6.1.  Since the last report 42 authors have pushed 326 commits to master.

6.2.  Documentation- Architecture guides, How To’s, Tutorials, and APIs
have been improved.

6.3.  More features (e.g. operators) requested by the user community has
been added.

6.4.   A new Perl language binding for MXNet was added.



7. How does the podling rate their own maturity. Maturity = Low.





On Mon, Jul 3, 2017 at 3:49 AM,  wrote:

> Dear podling,
>
> This email was sent by an automated system on behalf of the Apache
> Incubator PMC. It is an initial reminder to give you plenty of time to
> prepare your quarterly board report.
>
> The board meeting is scheduled for Wed, 19 July 2017, 10:30 am PDT.
> The report for your podling will form a part of the Incubator PMC
> report. The Incubator PMC requires your report to be submitted 2 weeks
> before the board meeting, to allow sufficient time for review and
> submission (Wed, July 05).
>
> Please submit your report with sufficient time to allow the Incubator
> PMC, and subsequently board members to review and digest. Again, the
> very latest you should submit your report is 2 weeks prior to the board
> meeting.
>
> Thanks,
>
> The Apache Incubator PMC
>
> Submitting your Report
>
> --
>
> Your report should contain the following:
>
> *   Your project name
> *   A brief description of your project, which assumes no knowledge of
> the project or necessarily of its field
> *   A list of the three most important issues to address in the move
> towards graduation.
> *   Any issues that the Incubator PMC or ASF Board might wish/need to be
> aware of
> *   How has the community developed since the last report
> *   How has the project developed since the last report.
> *   How does the podling rate their own maturity.
>
> This should be appended to the Incubator Wiki page at:
>
> https://wiki.apache.org/incubator/July2017
>
> Note: This is manually populated. You may need to wait a little before
> this page is created