RE: [DISCUSSION] Spinoff ANN package
Thanks for your volunteering! I'll add you. BTW, please don't forget: you're currently a chair of Apache Hama and it's important role. :-) -- Best Regards, Edward J. Yoon -Original Message- From: Chia-Hung Lin [mailto:cli...@googlemail.com] Sent: Wednesday, August 05, 2015 1:08 PM To: dev@hama.apache.org Subject: Re: [DISCUSSION] Spinoff ANN package +1 That looks interesting. I would like to participate in this project. On 5 August 2015 at 11:52, Edward J. Yoon edwardy...@apache.org wrote: Guys, I plan to submit a 'DNN platform on top of Apache Hama' proposal as below. I know Hama community is somewhat small, but the main reason is that this domain-specific project is not fit for Apache Hama community. Recruiting volunteers is also hard problem. I expect this will become a very nice use-case of Apache Hama. If you have any suggestions or other opinions, Please let me know. Also, if you want to participate in this project, Pls feel free to add your name here. Thanks! -- == Abstract == (tentatively named Horn [h?:n], korean meaning of Horn is a Spirit) is a neuron-centric programming APIs and execution framework for large-scale deep learning, built on top of Apache Hama. == Proposal == It is a goal of the Horn to provide a neuron-centric programming APIs which allows user to easily define the characteristic of artificial neural network model and its structure, and its execution framework that leverages the heterogeneous resources on Hama and Hadoop YARN cluster. == Background == The initial ANN code was developed at Apache Hama project by a committer, Yexi Jiang (Facebook) in 2013. The motivation behind this work is to build a framework that provides more intuitive programming APIs like Google's MapReduce or Pregel and supports applications needing large model with huge memory consumptions in distributed way. == Rationale == While many of deep learning open source softwares are still data or model parallel only, we aim to support both data and model parallelism and also fault-tolerant system design. The basic idea of data and model parallelism is use of the remote parameter server to parallelize model creation and distribute training across machines, and the BSP framework of Apache Hama for performing asynchronous mini-batches. Within single BSP job, each task group works asynchronously using region barrier synchronization instead of global barrier synchronization, and trains large-scale neural network model using assigned data sets in BSP paradigm. This architecture is inspired by Google's DistBelief (Jeff Dean et al, 2012). == Initial Goals == Some current goals include: * builds new community * provides more intuitive programming APIs * needs both data and model parallelism support * must run natively on both Hama and Hadoop2 * needs also GPUs and InfiniBand support == Current Status == === Meritocracy === The core developers understand what it means to have a process based on meritocracy. We will provide continuous efforts to build an environment that supports this, encouraging community members to contribute. === Community === A small community has formed within the Apache Hama project and some companies such as instant messenger service company and mobile manufacturing company. And many people are interested in the large-scale deep learning platform itself. By bringing Horn into Apache, we believe that the community will grow even bigger. === Core Developers === Edward J. Yoon, Thomas Jungblut, and Dongjin Lee == Known Risks == === Orphaned Products === Apache Hama is already a core open source component at Samsung Electronics, and Horn also will be used by Samsung Electronics, and so there is no direct risk for this project to be orphaned. === Inexperience with Open Source === Some are very new and the others have experience using and/or working on Apache open source projects. === Homogeneous Developers === The initial committers are from different organizations such as, Microsoft, Samsung Electronics, and Line Plus. === Reliance on Salaried Developers === Other developers will also start working on the project in their spare time. === Relationships with Other Apache Products === * Horn is based on Apache Hama * Apache Zookeeper is used for distributed locking service * Natively run on Apache Hadoop and Mesos * Horn can be somewhat overlapped with Singa podling. === An Excessive Fascination with the Apache Brand === Horn itself will hopefully have benefits from Apache, in terms of attracting a community and establishing a solid group of developers, but also the relation with Apache Hama, a general-purpose BSP computing engine. These are the main reasons for us to send this proposal. == Documentation == Initial plan about Horn can be found at http://blog.udanax.org/2015/06/googles-distbelief-clone-project-on.html == Initial Source == The initial source
Re: [DISCUSSION] Spinoff ANN package
+1 That looks interesting. I would like to participate in this project. On 5 August 2015 at 11:52, Edward J. Yoon edwardy...@apache.org wrote: Guys, I plan to submit a 'DNN platform on top of Apache Hama' proposal as below. I know Hama community is somewhat small, but the main reason is that this domain-specific project is not fit for Apache Hama community. Recruiting volunteers is also hard problem. I expect this will become a very nice use-case of Apache Hama. If you have any suggestions or other opinions, Please let me know. Also, if you want to participate in this project, Pls feel free to add your name here. Thanks! -- == Abstract == (tentatively named Horn [hɔ:n], korean meaning of Horn is a Spirit) is a neuron-centric programming APIs and execution framework for large-scale deep learning, built on top of Apache Hama. == Proposal == It is a goal of the Horn to provide a neuron-centric programming APIs which allows user to easily define the characteristic of artificial neural network model and its structure, and its execution framework that leverages the heterogeneous resources on Hama and Hadoop YARN cluster. == Background == The initial ANN code was developed at Apache Hama project by a committer, Yexi Jiang (Facebook) in 2013. The motivation behind this work is to build a framework that provides more intuitive programming APIs like Google's MapReduce or Pregel and supports applications needing large model with huge memory consumptions in distributed way. == Rationale == While many of deep learning open source softwares are still data or model parallel only, we aim to support both data and model parallelism and also fault-tolerant system design. The basic idea of data and model parallelism is use of the remote parameter server to parallelize model creation and distribute training across machines, and the BSP framework of Apache Hama for performing asynchronous mini-batches. Within single BSP job, each task group works asynchronously using region barrier synchronization instead of global barrier synchronization, and trains large-scale neural network model using assigned data sets in BSP paradigm. This architecture is inspired by Google's DistBelief (Jeff Dean et al, 2012). == Initial Goals == Some current goals include: * builds new community * provides more intuitive programming APIs * needs both data and model parallelism support * must run natively on both Hama and Hadoop2 * needs also GPUs and InfiniBand support == Current Status == === Meritocracy === The core developers understand what it means to have a process based on meritocracy. We will provide continuous efforts to build an environment that supports this, encouraging community members to contribute. === Community === A small community has formed within the Apache Hama project and some companies such as instant messenger service company and mobile manufacturing company. And many people are interested in the large-scale deep learning platform itself. By bringing Horn into Apache, we believe that the community will grow even bigger. === Core Developers === Edward J. Yoon, Thomas Jungblut, and Dongjin Lee == Known Risks == === Orphaned Products === Apache Hama is already a core open source component at Samsung Electronics, and Horn also will be used by Samsung Electronics, and so there is no direct risk for this project to be orphaned. === Inexperience with Open Source === Some are very new and the others have experience using and/or working on Apache open source projects. === Homogeneous Developers === The initial committers are from different organizations such as, Microsoft, Samsung Electronics, and Line Plus. === Reliance on Salaried Developers === Other developers will also start working on the project in their spare time. === Relationships with Other Apache Products === * Horn is based on Apache Hama * Apache Zookeeper is used for distributed locking service * Natively run on Apache Hadoop and Mesos * Horn can be somewhat overlapped with Singa podling. === An Excessive Fascination with the Apache Brand === Horn itself will hopefully have benefits from Apache, in terms of attracting a community and establishing a solid group of developers, but also the relation with Apache Hama, a general-purpose BSP computing engine. These are the main reasons for us to send this proposal. == Documentation == Initial plan about Horn can be found at http://blog.udanax.org/2015/06/googles-distbelief-clone-project-on.html == Initial Source == The initial source code has been release as part of Apache Hama project developed under Apache Software Foundation. The source code is currently hosted at https://svn.apache.org/repos/asf/hama/trunk/ml/src/main/java/org/apache/hama/ml/ann/ == Cryptography == Not applicable. == Required Resources == Mailing Lists * horn-private * horn-dev Subversion Directory *
Jenkins build is back to normal : Hama-Nightly-for-Hadoop-2.x #688
See https://builds.apache.org/job/Hama-Nightly-for-Hadoop-2.x/688/
