[ANNOUNCE] Apache SINGA (incubating) 0.1.0 released

[Wang Wei <wa...@comp.nus.edu.sg>]

We are pleased to announce that Apache SINGA (incubating) 0.1.0 is
released.

SINGA is a general distributed deep learning platform for training big deep
learning models over large datasets. It is designed with an intuitive
programming model based on the layer abstraction. SINGA supports a wide
variety of popular deep learning models.

The release is available at:
http://singa.apache.org/downloads.html

The main features of this release include

   - Both synchronous and asynchronous distributed training frameworks are
   supported, e.g., Hogwild!, AllReduce, Downpour, etc.
   - All three categories of popular deep learning models are supported,
   namely, feed-forward neural networks (e.g., CNN, MLP), recurrent neural
   networks and energy models (e.g, RBM).
   - Amazon EC2 image and GNU installation tool are provided for users to
   get started easily

We look forward to hearing your feedbacks, suggestions, and contributions
to the project.

Features for the next version will include

   - Mesos and Docker integration
   - Single node with Multi-GPU
   - Configuration helper and Python Binding
   - Model partitioning/parallelism


On behalf of the SINGA team,
Wei Wang

Re: [ANNOUNCE] Apache SINGA (incubating) 0.1.0 released

[Thejas Nair <th...@gmail.com>]

Congrats on the first release as apache project!


On Thu, Oct 8, 2015 at 1:31 AM, Wang Wei <wa...@comp.nus.edu.sg> wrote:
> We are pleased to announce that Apache SINGA (incubating) 0.1.0 is
> released.
>
> SINGA is a general distributed deep learning platform for training big deep
> learning models over large datasets. It is designed with an intuitive
> programming model based on the layer abstraction. SINGA supports a wide
> variety of popular deep learning models.
>
> The release is available at:
> http://singa.apache.org/downloads.html
>
> The main features of this release include
>
>    - Both synchronous and asynchronous distributed training frameworks are
>    supported, e.g., Hogwild!, AllReduce, Downpour, etc.
>    - All three categories of popular deep learning models are supported,
>    namely, feed-forward neural networks (e.g., CNN, MLP), recurrent neural
>    networks and energy models (e.g, RBM).
>    - Amazon EC2 image and GNU installation tool are provided for users to
>    get started easily
>
> We look forward to hearing your feedbacks, suggestions, and contributions
> to the project.
>
> Features for the next version will include
>
>    - Mesos and Docker integration
>    - Single node with Multi-GPU
>    - Configuration helper and Python Binding
>    - Model partitioning/parallelism
>
>
> On behalf of the SINGA team,
> Wei Wang