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.n...@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.sapu...@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 <j...@apache.org <javascript:;>> > wrote: > >> On Friday, February 27, 2015, Henry Saputra <henry.sapu...@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.n...@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, <oo...@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.sapu...@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: oo...@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.n...@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.n...@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.sapu...@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.n...@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 nusi...@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. > >>> >>>>>>> > >>> >>>>>>> > >>> --------------------------------------------------------------------- > >>> >>>>>>> To unsubscribe, e-mail: > general-unsubscr...@incubator.apache.org <javascript:;> > >>> <javascript:;> > >>> >>>>>>> For additional commands, e-mail: > general-h...@incubator.apache.org <javascript:;> > >>> <javascript:;> > >>> >>>>>>> > >>> >>>>>> > >>> >>>>>> > >>> --------------------------------------------------------------------- > >>> >>>>>> To unsubscribe, e-mail: > general-unsubscr...@incubator.apache.org <javascript:;> > >>> <javascript:;> > >>> >>>>>> For additional commands, e-mail: > general-h...@incubator.apache.org <javascript:;> > >>> <javascript:;> > >>> >>>>>> > >>> >>>> > >>> >>>> > --------------------------------------------------------------------- > >>> >>>> To unsubscribe, e-mail: general-unsubscr...@incubator.apache.org > <javascript:;> > >>> <javascript:;> > >>> >>>> For additional commands, e-mail: > general-h...@incubator.apache.org <javascript:;> > >>> <javascript:;> > >>> >>>> > >>> >>> > >>> >>> > >>> >>> > >>> >> > >>> > > >>> > --------------------------------------------------------------------- > >>> > To unsubscribe, e-mail: general-unsubscr...@incubator.apache.org > <javascript:;> > >>> <javascript:;> > >>> > For additional commands, e-mail: general-h...@incubator.apache.org > <javascript:;> > >>> <javascript:;> > >>> > > >>> > >>> --------------------------------------------------------------------- > >>> To unsubscribe, e-mail: general-unsubscr...@incubator.apache.org > <javascript:;> > >>> <javascript:;> > >>> For additional commands, e-mail: general-h...@incubator.apache.org > <javascript:;> > >>> <javascript:;> > >>> > >>> > >> > >> -- > >> Sent from My iPad, sorry for any misspellings. > > > > --------------------------------------------------------------------- > > To unsubscribe, e-mail: general-unsubscr...@incubator.apache.org > <javascript:;> > > For additional commands, e-mail: general-h...@incubator.apache.org > <javascript:;> > > > > --------------------------------------------------------------------- > To unsubscribe, e-mail: general-unsubscr...@incubator.apache.org > <javascript:;> > For additional commands, e-mail: general-h...@incubator.apache.org > <javascript:;> > >
