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From Henry Saputra <henry.sapu...@gmail.com>
Subject Re: [DISCUSS] [PROPOSAL] Singa for Apache Incubator
Date Fri, 27 Feb 2015 15:54:12 GMT
Thanks for the response, Thejas. Glad you have tried soliciting more
mentors.
Hopefully some of them bite.

On Friday, February 27, 2015, Thejas Nair <thejas.nair@gmail.com> wrote:

> Thanks for your inputs Henry.
> I did send personal emails to two folks (outside of Hortonworks) who
> seemed to be interested in the project, but that didn't help.  I have
> also been soliciting more mentors in this thread as well. I will try
> reaching out to folks who are in the intersection of incubator and
> mahout (or spark-ml) to see if they might be interested (hopefully
> people working on related projects are more likely to join in).
> Any other suggestions for soliciting more diverse set of mentors are
> also welcome.
>
> Regarding the diversity of initial set of committers, growing that
> should be easier once the project is an apache incubator project.  I
> see a strong desire to grow the community in the people who are
> currently working on the project.
>
>
>
> On Thu, Feb 26, 2015 at 11:42 PM, Henry Saputra <henry.saputra@gmail.com
> <javascript:;>> wrote:
> > I was not actually talking about requirement, but for the sake of
> > podling itself.
> >
> > If all initial mentors coming from same company, the risk of all of
> > them absent are greater because all will be subjected to same schedule
> > and priorities from their daytime employers. Especially for release
> > VOTEs. Three initial mentors wont be enough for this project, I think.
> >
> > Not too worries about initial committers coming from same org, but I
> > have seen that podling that does not have initial community will
> > struggle to thrive.
> >
> > Just 2-cents from my experience in incubator.
> >
> > - Henry
> >
> > On Thu, Feb 26, 2015 at 11:37 PM, jan i <jani@apache.org <javascript:;>>
> wrote:
> >> On Friday, February 27, 2015, Henry Saputra <henry.saputra@gmail.com
> <javascript:;>> wrote:
> >>
> >>> I am strongly suggest you solicit more (diverse) mentors before start
> the
> >>> VOTE.
> >>>
> >>> All initial committers are from same org and all initial mentors are
> >>> from same company (HW).
> >>
> >> We do have a requirement for diversity, for me all initial committers
> from
> >> the same company is just as big a problem as mentors. when everyone
> >> involved are from the same company then that signals a serious problem
> >> which should be addressed before starting a vote.
> >>
> >> rgds
> >> jan i
> >>
> >>>
> >>> I am not sure this is a good start for Apache podling.
> >>>
> >>>
> >>> - Henry
> >>>
> >>> On Thu, Feb 26, 2015 at 9:12 AM, Thejas Nair <thejas.nair@gmail.com
> <javascript:;>
> >>> <javascript:;>> wrote:
> >>> > The incubator proposal has been updated with the feedback so far.
> >>> > We have 3 mentors now, but I think it would be good to have
> additional
> >>> > mentors. Please let me know if anyone is able to help mentor this
> >>> > project.
> >>> >
> >>> > I am planning to start a vote on the proposal in a day or two.
> >>> >
> >>> >
> >>> > On Fri, Feb 6, 2015 at 5:21 PM,  <ooibc@comp.nus.edu.sg
> <javascript:;> <javascript:;>>
> >>> wrote:
> >>> >>
> >>> >> Regarding the number of users using this project -- at this moment,
> the
> >>> >> community is not big.  A few local start-ups have been trying to
> use it
> >>> >> (mainly due to announcement in our seminar list), eg. one is using
> it
> >>> for
> >>> >> image recognition (given a phone snapped by a user, it wants to
be
> >>> return
> >>> >> the same the product, and a list of similar products, such as a
> luxury
> >>> bag
> >>> >> on a passerby).  Researchers from outside of NUS may have been
> using it
> >>> >> since we published an application paper on cross domain/modal
> retrieval
> >>> in
> >>> >> VLDB 2014.
> >>> >>
> >>> >> We have not announced the project to the outside community yet
-- we
> >>> would
> >>> >> announce it in dbworld etc in due course.
> >>> >>
> >>> >> Thanks and have a good weekend.
> >>> >>
> >>> >> regards
> >>> >> beng chin
> >>> >>
> >>> >>>
> >>> >>> Thanks for the comments and suggestions.
> >>> >>> With permission from Thejas, I would like to respond to point
2.
> >>> >>>
> >>> >>> We have a huge team down at NUS (National University of Singapore)
> --
> >>> >>> we have about seven database/data mining data professors (not
> including
> >>> >>> those in systems, networking, and machine learning).
> >>> >>> I myself have nine PhD students in a steady state, and I have
a few
> >>> large
> >>> >>> grants, with a total budget of about 15 million S$ (~12 million
> USD),
> >>> that
> >>> >>> allows me to hire a number of research fellows and research
> assistants
> >>> for
> >>> >>> the next few years.  In a constant state, I have about 20 people
> (PhD
> >>> >>> students/RA/RF) working with me alone.  Other professors have
> their own
> >>> >>> grants (unlike other countries, it is relatively easy to get
large
> >>> grants
> >>> >>> in Singapore; many overseas Universities, including UIUC, MIT,
ETH
> etc
> >>> >>> have research labs funded by Singapore Research Foundation
> [equivalent
> >>> of
> >>> >>> NSF]).
> >>> >>>
> >>> >>> SINGA is a long term project for us -- while it is a platform
as it
> >>> is, we
> >>> >>> are using it for healthcare predictive analytics (by working
with a
> >>> >>> hospital associated with the University).  Therefore, we will
be
> >>> working
> >>> >>> on SINGA, not solely as a distributed DL platform, but as a
tool
> that
> >>> will
> >>> >>> enable us to do data analytics on some business domains (eg.
> >>> healthcase,
> >>> >>> consumer etc)
> >>> >>>
> >>> >>> For the initial set of committers, three are tenured professors,
> five
> >>> are
> >>> >>> students, with 2-5 years to go before they complete their PhD.
> Quite
> >>> >>> often, some would stay back as a research fellow for a couple
of
> years
> >>> >>> before they start looking for a job outside.  We will work
with
> mentors
> >>> >>> and new developers (from outside of NUS or Zhejiang University)
in
> >>> >>> enhancing the system.
> >>> >>>
> >>> >>> The project should survive in that sense.
> >>> >>>
> >>> >>> (I have an on-going project CIIDAA that has been around since
> 2008; it
> >>> was
> >>> >>> started as another project, epiC,  with a different grant,
and
> then we
> >>> >>> continue the development with a new grant for CIIDAA --
> >>> >>> http://www.comp.nus.edu.sg/~ciidaa/
> >>> >>> )
> >>> >>>
> >>> >>> Thanks.
> >>> >>>
> >>> >>> regards
> >>> >>> beng chin
> >>> >>> ps: i am not sure if my email will get through to the group.
> >>> >>>
> >>> >>>
> >>> >>> ---------------------------- Original Message
> >>> ----------------------------
> >>> >>> Subject: Re: [DISCUSS] [PROPOSAL] Singa for Apache Incubator
> >>> >>> From:    "Henry Saputra" <henry.saputra@gmail.com <javascript:;>
> <javascript:;>>
> >>> >>> Date:    Thu, February 5, 2015 2:57 pm
> >>> >>> To:      "general@incubator.apache.org <javascript:;>
> <javascript:;>" <
> >>> general@incubator.apache.org <javascript:;> <javascript:;>>
> >>> >>> Cc:      ooibc@comp.nus.edu.sg <javascript:;> <javascript:;>
> >>> >>>
> >>>
> --------------------------------------------------------------------------
> >>> >>>
> >>> >>> Several comments:
> >>> >>> -) How many users already using this project? I would reccomend
to
> >>> >>> drop request for singa-user list at the beginning.
> >>> >>> -) All the initial committers come from university and seemed
like
> >>> >>> some of them already ready to leave university. I am not too
sure
> if
> >>> >>> this project go survive if all of the inital committers are
from
> >>> >>> university as students.
> >>> >>> -) Need to solicit more mentors if this project ever get to
Apache
> >>> >>> incubator.
> >>> >>>
> >>> >>> - Henry
> >>> >>>
> >>> >>> On Tue, Feb 3, 2015 at 3:58 PM, Thejas Nair <thejas.nair@gmail.com
> <javascript:;>
> >>> <javascript:;>> wrote:
> >>> >>>> The "Relationship with Other Apache Products" section has
been
> >>> >>>> updated. The reference to H2O in that section has been
removed,
> and
> >>> >>>> other projects have been added.
> >>> >>>>  Thanks for the feedback!
> >>> >>>>
> >>> >>>>
> >>> >>>> On Wed, Jan 28, 2015 at 10:27 AM, Thejas Nair <
> thejas.nair@gmail.com <javascript:;>
> >>> <javascript:;>>
> >>> >>> wrote:
> >>> >>>>> Thanks for pointing that out Henry! Yes, looks like
H20 is not an
> >>> >>>>> apache project, I should have verified that.
> >>> >>>>> I will edit that, and revisit that section along with
the folks
> in
> >>> >>>>> Singa community.
> >>> >>>>>
> >>> >>>>>
> >>> >>>>> On Tue, Jan 27, 2015 at 6:55 PM, Henry Saputra
> >>> >>> <henry.saputra@gmail.com <javascript:;> <javascript:;>>
wrote:
> >>> >>>>>> Quick immediate comment that "Apache H2O" is not
really Apache
> >>> >>>>>> project.
> >>> >>>>>>
> >>> >>>>>> I assume you are referring to https://github.com/h2oai/h2o
(or
> >>> >>>>>> https://github.com/h2oai/h2o-dev) ?
> >>> >>>>>>
> >>> >>>>>> - Henry
> >>> >>>>>>
> >>> >>>>>> On Tue, Jan 27, 2015 at 5:29 PM, Thejas Nair <
> thejas.nair@gmail.com <javascript:;>
> >>> <javascript:;>>
> >>> >>> wrote:
> >>> >>>>>>> Hello everyone,
> >>> >>>>>>>
> >>> >>>>>>> I would like to propose the inclusion of Singa
as an Apache
> >>> Incubator
> >>> >>> project.
> >>> >>>>>>>
> >>> >>>>>>> Here is the proposal -
> >>> >>>>>>> https://wiki.apache.org/incubator/SingaProposal
> >>> >>>>>>>
> >>> >>>>>>> Please review the proposal and give feedback.
I am planning to
> >>> start
> >>> >>>>>>> a
> >>> >>>>>>> vote after 7 days if the proposal looks good.
> >>> >>>>>>> We are also seeking additional Apache mentors
for the project.
> >>> >>>>>>>
> >>> >>>>>>> Thanks,
> >>> >>>>>>> Thejas
> >>> >>>>>>> ==========================================================
> >>> >>>>>>> Singa Incubator Proposal
> >>> >>>>>>>
> >>> >>>>>>> Abstract
> >>> >>>>>>>
> >>> >>>>>>> SINGA is a distributed deep learning platform.
> >>> >>>>>>>
> >>> >>>>>>> Proposal
> >>> >>>>>>>
> >>> >>>>>>> SINGA is an efficient, scalable and easy-to-use
distributed
> >>> platform
> >>> >>>>>>> for training deep learning models, e.g., Deep
Convolutional
> Neural
> >>> >>>>>>> Network and Deep Belief Network. It parallelizes
the
> computation
> >>> >>>>>>> (i.e., training) onto a cluster of nodes by
distributing the
> >>> training
> >>> >>>>>>> data and model automatically to speed up the
training. Built-in
> >>> >>>>>>> training algorithms like Back-Propagation and
Contrastive
> >>> Divergence
> >>> >>>>>>> are implemented based on common abstractions
of deep learning
> >>> models.
> >>> >>>>>>> Users can train their own deep learning models
by simply
> >>> customizing
> >>> >>>>>>> these abstractions like implementing the Mapper
and Reducer in
> >>> >>>>>>> Hadoop.
> >>> >>>>>>>
> >>> >>>>>>> Background
> >>> >>>>>>>
> >>> >>>>>>> Deep learning refers to a set of feature (or
representation)
> >>> learning
> >>> >>>>>>> models that consist of multiple (non-linear)
layers, where
> >>> different
> >>> >>>>>>> layers learn different levels of abstractions
> (representations) of
> >>> >>>>>>> the
> >>> >>>>>>> raw input data. Larger (in terms of model parameters)
and
> deeper
> >>> (in
> >>> >>>>>>> terms of number of layers) models have shown
better
> performance,
> >>> >>>>>>> e.g.,
> >>> >>>>>>> lower image classification error in Large Scale
Visual
> Recognition
> >>> >>>>>>> Challenge. However, a larger model requires
more memory and
> larger
> >>> >>>>>>> training data to reduce over-fitting. Complex
numeric
> operations
> >>> make
> >>> >>>>>>> the training computation intensive. In practice,
training large
> >>> deep
> >>> >>>>>>> learning models takes weeks or months on a
single node (even
> with
> >>> >>>>>>> GPU).
> >>> >>>>>>>
> >>> >>>>>>> Rational
> >>> >>>>>>>
> >>> >>>>>>> Deep learning has gained a lot of attraction
in both academia
> and
> >>> >>>>>>> industry due to its success in a wide range
of areas such as
> >>> computer
> >>> >>>>>>> vision and speech recognition. However, training
of such
> models is
> >>> >>>>>>> computationally expensive, especially for large
and deep models
> >>> >>>>>>> (e.g.,
> >>> >>>>>>> with billions of parameters and more than 10
layers). Both
> Google
> >>> and
> >>> >>>>>>> Microsoft have developed distributed deep learning
systems to
> make
> >>> >>>>>>> the
> >>> >>>>>>> training more efficient by distributing the
computations
> within a
> >>> >>>>>>> cluster of nodes. However, these systems are
closed source
> >>> softwares.
> >>> >>>>>>> Our goal is to leverage the community of open
source
> developers to
> >>> >>>>>>> make SINGA efficient, scalable and easy to
use. SINGA is a full
> >>> >>>>>>> fledged distributed platform, that could benefit
the community
> and
> >>> >>>>>>> also benefit from the community in their involvement
in
> >>> contributing
> >>> >>>>>>> to the further work in this area. We believe
the nature of
> SINGA
> >>> and
> >>> >>>>>>> our visions for the system fit naturally to
Apache's
> philosophy and
> >>> >>>>>>> development framework.
> >>> >>>>>>>
> >>> >>>>>>> Initial Goals
> >>> >>>>>>>
> >>> >>>>>>> We have developed a system for SINGA running
on a commodity
> >>> computer
> >>> >>>>>>> cluster. The initial goals include, * improving
the system in
> terms
> >>> >>>>>>> of
> >>> >>>>>>> scalability and efficiency, e.g., using Infiniband
for network
> >>> >>>>>>> communication and multi-threading for one node
computation. We
> >>> would
> >>> >>>>>>> consider extending SINGA to GPU clusters later.
* benchmarking
> with
> >>> >>>>>>> larger datasets (hundreds of millions of training
instances)
> and
> >>> >>>>>>> models (billions of parameters). * adding more
built-in deep
> >>> learning
> >>> >>>>>>> models. Users can train the built-in models
on their datasets
> >>> >>>>>>> directly.
> >>> >>>>>>>
> >>> >>>>>>> Current Status
> >>> >>>>>>>
> >>> >>>>>>> Meritocracy
> >>> >>>>>>>
> >>> >>>>>>> We would like to follow ASF meritocratic principles
to
> encourage
> >>> more
> >>> >>>>>>> developers to contribute in this project. We
know that only
> active
> >>> >>>>>>> and
> >>> >>>>>>> excellent developers can make SINGA a successful
project. The
> >>> >>>>>>> committer list and PMC will be updated based
on developers'
> >>> >>>>>>> performance and commitment. We are also improving
the
> documentation
> >>> >>>>>>> and code to help new developers get started
quickly.
> >>> >>>>>>>
> >>> >>>>>>> Community
> >>> >>>>>>>
> >>> >>>>>>> SINGA is currently being developed in the Database
System
> Research
> >>> >>>>>>> Lab
> >>> >>>>>>> at the National University of Singapore (NUS)
in collaboration
> with
> >>> >>>>>>> Zhejiang University in China. Our lab has extensive
experience
> in
> >>> >>>>>>> building database related systems, including
distributed
> systems.
> >>> Six
> >>> >>>>>>> PhD students and research assistants (Jinyang
Gao, Kaiping
> Zheng,
> >>> >>>>>>> Sheng Wang, Wei Wang, Zhaojing Luo and Zhongle
Xie) , a
> research
> >>> >>>>>>> fellow (Anh Dinh) and three professors (Beng
Chin Ooi, Gang
> Chen,
> >>> >>>>>>> Kian
> >>> >>>>>>> Lee Tan) have been working for a year on this
project. We are
> open
> >>> to
> >>> >>>>>>> recruiting more developers from diverse backgrounds.
> >>> >>>>>>>
> >>> >>>>>>> Core Developers
> >>> >>>>>>>
> >>> >>>>>>> Beng Chin Ooi, Gang Chen and Kian Lee Tan are
professors who
> have
> >>> >>>>>>> worked on distributed systems for more than
20 years. They have
> >>> >>>>>>> collaborated with the industry and have built
various large
> scale
> >>> >>>>>>> systems. Anh Dinh's research is also on distributed
systems,
> albeit
> >>> >>>>>>> with more focus on security aspects. Wei Wang's
research is on
> deep
> >>> >>>>>>> learning problems including deep learning applications
and
> large
> >>> >>>>>>> scale
> >>> >>>>>>> training. Sheng Wang and Jinyang are working
on efficient
> indexing,
> >>> >>>>>>> querying of large scale data and machine learning.
Kaiping,
> >>> Zhaojing
> >>> >>>>>>> and Zhongle are new PhD students who jointed
SINGA recently.
> They
> >>> >>>>>>> will
> >>> >>>>>>> work on this project for a longer time (next
4-5 years). While
> we
> >>> >>>>>>> share common research interests, each member
also brings
> diverse
> >>> >>>>>>> expertise to the team.
> >>> >>>>>>>
> >>> >>>>>>> Alignment
> >>> >>>>>>>
> >>> >>>>>>> ASF is already the home of many distributed
platforms, e.g.,
> >>> Hadoop,
> >>> >>>>>>> Spark and Mahout, each of which targets a different
application
> >>> >>>>>>> domain. SINGA, being a distributed platform
for large-scale
> deep
> >>> >>>>>>> learning, focuses on another important domain
for which there
> still
> >>> >>>>>>> lacks a robust and scalable open-source platform.
The recent
> >>> success
> >>> >>>>>>> of deep learning models especially for vision
and speech
> >>> recognition
> >>> >>>>>>> tasks has generated interests in both applying
existing deep
> >>> learning
> >>> >>>>>>> models and in developing new ones. Thus, an
open-source
> platform
> >>> for
> >>> >>>>>>> deep learning will be able to attract a large
community of
> users
> >>> and
> >>> >>>>>>> developers. SINGA is a complex system needing
many iterations
> of
> >>> >>>>>>> design, implementation and testing. Apache's
collaboration
> >>> framework
> >>> >>>>>>> which encourages active contribution from developers
will
> >>> inevitably
> >>> >>>>>>> help improve the quality of the system, as
shown in the
> success of
> >>> >>>>>>> Hadoop, Spark, etc.. Equally important is the
community of
> users
> >>> >>>>>>> which
> >>> >>>>>>> helps identify real-life applications of deep
learning, and
> helps
> >>> to
> >>> >>>>>>> evaluate the system's performance and ease-of-use.
We hope to
> >>> >>>>>>> leverage
> >>> >>>>>>> ASF for coordinating and promoting both communities,
and in
> return
> >>> >>>>>>> benefit the communities with another useful
tool.
> >>> >>>>>>>
> >>> >>>>>>> Known Risks
> >>> >>>>>>>
> >>> >>>>>>> Orphaned products
> >>> >>>>>>>
> >>> >>>>>>> Four core developers (Anh, Wei Wang, Jinyang
and Sheng Wang)
> may
> >>> >>>>>>> leave
> >>> >>>>>>> the lab in two to four years time. It is possible
that some of
> them
> >>> >>>>>>> may not have enough time to focus on this project
after that.
> But,
> >>> >>>>>>> SINGA is part of our other bigger research
projects on
> building an
> >>> >>>>>>> infrastructure for data intensive applications,
which include
> >>> >>>>>>> health-care analytics and brain-inspired computing.
Beng Chin
> and
> >>> >>>>>>> Kian
> >>> >>>>>>> Lee would continue working on it and getting
more people
> involved.
> >>> >>>>>>> For
> >>> >>>>>>> example, three new developers (Kaiping, Zhaojing
and Zhongle)
> >>> joined
> >>> >>>>>>> us recently. Individual developers are welcome
to make SINGA a
> >>> >>>>>>> diverse
> >>> >>>>>>> community that is robust and independent from
any single
> developer.
> >>> >>>>>>>
> >>> >>>>>>> Inexperience with Open Source
> >>> >>>>>>>
> >>> >>>>>>> All the developers are active users and followers
of open
> source
> >>> >>>>>>> projects. Our research lab has a strong commitment
to open
> source,
> >>> >>>>>>> and
> >>> >>>>>>> has released the source code of several systems
under open
> source
> >>> >>>>>>> license as a way of contributing back to the
open source
> community.
> >>> >>>>>>> But we do not have much real experience in
open source projects
> >>> with
> >>> >>>>>>> large and well organized communities like those
in Apache.
> This is
> >>> >>>>>>> one
> >>> >>>>>>> reason we choose Apache which is experienced
in open source
> project
> >>> >>>>>>> incubation. We hope to get the help from Apache
(e.g.,
> champion and
> >>> >>>>>>> mentors) to establish a healthy path for SINGA.
> >>> >>>>>>>
> >>> >>>>>>> Homogenous Developers
> >>> >>>>>>>
> >>> >>>>>>> Although the current developers are researchers
in the
> >>> universities,
> >>> >>>>>>> they have different research interests and
project
> experiences, as
> >>> >>>>>>> mentioned in the section that introduces the
core developers.
> We
> >>> know
> >>> >>>>>>> that a diverse community is helpful. Hence
we are open to the
> idea
> >>> of
> >>> >>>>>>> recruiting developers from other regions and
organizations.
> >>> >>>>>>>
> >>> >>>>>>> Reliance on Salaried Developers
> >>> >>>>>>>
> >>> >>>>>>> As a research project in the university, SINGA's
current
> developing
> >>> >>>>>>> community consists of professors, PhD students,
research
> assistants
> >>> >>>>>>> and postdoctoral fellows. They are driven by
their interests to
> >>> work
> >>> >>>>>>> on this project and have contributed actively
since the start
> of
> >>> the
> >>> >>>>>>> project. The research assistants and fellows
are expected to
> leave
> >>> >>>>>>> when their contracts expire. However, they
are keen to
> continue to
> >>> >>>>>>> work on the project voluntarily. Moreover,
as a long term
> research
> >>> >>>>>>> project, new research assistants and fellows
are likely to
> join the
> >>> >>>>>>> project.
> >>> >>>>>>>
> >>> >>>>>>> A Excessive Fascination with the Apache Brand
> >>> >>>>>>>
> >>> >>>>>>> We choose Apache not for publicity. We have
two purposes.
> First, we
> >>> >>>>>>> want to leverage Apache's reputation to recruit
more
> developers to
> >>> >>>>>>> make a diverse community. Second, we hope that
Apache can help
> us
> >>> to
> >>> >>>>>>> establish a healthy path in developing SINGA.
Beng Chin and
> >>> Kian-Lee
> >>> >>>>>>> are established database and distributed system
researchers,
> and
> >>> >>>>>>> together with the other contributors, they
sincerely believe
> that
> >>> >>>>>>> there is a need for a widely accepted open
source distributed
> deep
> >>> >>>>>>> learning platform. The field of deep learning
is still at its
> >>> >>>>>>> infancy,
> >>> >>>>>>> and an open source platform will fuel the research
in the area.
> >>> >>>>>>> Moreover, such a platform will enable researchers
to develop
> new
> >>> >>>>>>> models and algorithms, rather than spending
time implementing a
> >>> deep
> >>> >>>>>>> learning system from scratch. Furthermore,
the need for
> scalability
> >>> >>>>>>> for such a platform is obvious.
> >>> >>>>>>>
> >>> >>>>>>> Relationship with Other Apache Products
> >>> >>>>>>>
> >>> >>>>>>> Apache H2O implemented two simple deep learning
models, namely
> the
> >>> >>>>>>> Multi-Layer Perceptron and Deep Auto-encoders.
There are two
> >>> >>>>>>> significant differences between H2O and SINGA.
First, H2O
> adopts
> >>> the
> >>> >>>>>>> Map-Reduce framework which runs a set of computing
nodes in
> >>> parallel
> >>> >>>>>>> againsts of the training set. Model parameters
trained by all
> >>> >>>>>>> computing nodes are averaged as the final model
parameters.
> This
> >>> >>>>>>> training algorithm is different from the distributed
training
> >>> >>>>>>> algorithm used by DistBelief, Adam and SINGA,
which frequently
> >>> >>>>>>> synchronizes the parameters trained from different
nodes. SINGA
> >>> >>>>>>> adopts
> >>> >>>>>>> the parameter server framework to support a
wide range of
> >>> distributed
> >>> >>>>>>> training algorithms and parallelization methods
(e.g., data
> >>> >>>>>>> parallelism, model parallelism and hybrid parallelism.
H2O only
> >>> >>>>>>> support data parallelism) . Second, in H2O,
users are
> restricted to
> >>> >>>>>>> use the two built-in models. In SINGA, we provide
simple
> >>> programming
> >>> >>>>>>> model to let users implement their own deep
learning models. A
> new
> >>> >>>>>>> deep learning model can be implemented by customizing
the base
> >>> Layer
> >>> >>>>>>> class for each layer involved in the model.
It is similar to
> >>> writing
> >>> >>>>>>> Hadoop programs where users only need to override
the base
> Mapper
> >>> and
> >>> >>>>>>> Reducer. We also provide built-in models for
users to use
> directly.
> >>> >>>>>>>
> >>> >>>>>>> Documentation
> >>> >>>>>>>
> >>> >>>>>>> The project is hosted at
> >>> >>>>>>> http://www.comp.nus.edu.sg/~dbsystem/project/singa.html.
> >>> >>>>>>> Documentations can be found at the Github Wiki
Page:
> >>> >>>>>>> https://github.com/nusinga/singa/wiki. We continue
to refine
> and
> >>> >>>>>>> improve the documentation.
> >>> >>>>>>>
> >>> >>>>>>> Initial Source
> >>> >>>>>>>
> >>> >>>>>>> We use Github to maintain our source code,
> >>> >>> https://github.com/nusinga/singa
> >>> >>>>>>>
> >>> >>>>>>> Source and Intellectual Property Submission
Plan
> >>> >>>>>>>
> >>> >>>>>>> We plan to make our code base be under Apache
License, Version
> 2.0.
> >>> >>>>>>>
> >>> >>>>>>> External Dependencies
> >>> >>>>>>>
> >>> >>>>>>> required by the core code base: glog, gflags,
google protobuf,
> >>> >>>>>>> open-blas, mpich, armci-mpi.
> >>> >>>>>>> required by data preparation and preprocessing:
opencv, hdfs,
> >>> python.
> >>> >>>>>>>
> >>> >>>>>>> Cryptography
> >>> >>>>>>>
> >>> >>>>>>> Not Applicable
> >>> >>>>>>>
> >>> >>>>>>> Required Resources
> >>> >>>>>>>
> >>> >>>>>>> Mailing Lists
> >>> >>>>>>>
> >>> >>>>>>> Currently, we use google group for internal
discussion. The
> mailing
> >>> >>>>>>> address is nusinga@googlegroup.com <javascript:;>
> <javascript:;>. We will
> >>> migrate the content to
> >>> >>>>>>> the
> >>> >>>>>>> apache mailing lists in the future.
> >>> >>>>>>>
> >>> >>>>>>> singa-dev
> >>> >>>>>>> singa-user
> >>> >>>>>>> singa-commits
> >>> >>>>>>> singa-private (for private discussion within
PCM)
> >>> >>>>>>>
> >>> >>>>>>> Git Repository
> >>> >>>>>>>
> >>> >>>>>>> We want to continue using git for version control.
Hence, a git
> >>> repo
> >>> >>>>>>> is required.
> >>> >>>>>>>
> >>> >>>>>>> Issue Tracking
> >>> >>>>>>>
> >>> >>>>>>> JIRA Singa (SINGA)
> >>> >>>>>>>
> >>> >>>>>>> Initial Committers
> >>> >>>>>>>
> >>> >>>>>>> Beng Chin Ooi (ooibc @comp.nus.edu.sg)
> >>> >>>>>>> Kian Lee Tan (tankl @comp.nus.edu.sg)
> >>> >>>>>>> Gang Chen (cg @zju.edu.cn)
> >>> >>>>>>> Wei Wang (wangwei @comp.nus.edu.sg)
> >>> >>>>>>> Dinh Tien Tuan Anh (dinhtta @comp.nus.edu.sg)
> >>> >>>>>>> Jinyang Gao (jinyang.gao @comp.nus.edu.sg)
> >>> >>>>>>> Sheng Wang (wangsh @comp.nus.edu.sg)
> >>> >>>>>>> Kaiping Zheng (kaiping @comp.nus.edu.sg)
> >>> >>>>>>> Zhaojing Luo (zhaojing @comp.nus.edu.sg)
> >>> >>>>>>> Zhongle Xie (zhongle @comp.nus.edu.sg)
> >>> >>>>>>>
> >>> >>>>>>> Affiliations
> >>> >>>>>>>
> >>> >>>>>>> Beng Chin Ooi, National University of Singapore
> >>> >>>>>>> Kian Lee Tan, National University of Singapore
> >>> >>>>>>> Gang Chen, Zhejiang University
> >>> >>>>>>> Wei Wang, National University of Singapore
> >>> >>>>>>> Dinh Tien Tuan Anh, National University of
Singapore
> >>> >>>>>>> Jinyang Gao, National University of Singapore
> >>> >>>>>>> Sheng Wang, National University of Singapore
> >>> >>>>>>> Kaiping Zheng, National University of Singapore
> >>> >>>>>>> Zhaojing Luo, National University of Singapore
> >>> >>>>>>> Zhongle Xie, National University of Singapore
> >>> >>>>>>>
> >>> >>>>>>> Sponsors
> >>> >>>>>>>
> >>> >>>>>>> Champion
> >>> >>>>>>>
> >>> >>>>>>> Thejas Nair (thejas at apache.org) - Hortonworks
> >>> >>>>>>>
> >>> >>>>>>> Nominated Mentors
> >>> >>>>>>>
> >>> >>>>>>> Thejas Nair (thejas at apache.org) - Hortonworks
> >>> >>>>>>> Alan Gates (gates at apache dot org) - Hortonworks
> >>> >>>>>>> (Seeking more volunteers!)
> >>> >>>>>>>
> >>> >>>>>>> Sponsoring Entity
> >>> >>>>>>>
> >>> >>>>>>> We are requesting the Incubator to sponsor
this project.
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