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From "wangwei (JIRA)" <j...@apache.org>
Subject [jira] [Created] (SINGA-162) Overview of features for V1.x
Date Mon, 02 May 2016 08:44:12 GMT
wangwei created SINGA-162:
-----------------------------

             Summary: Overview of features for V1.x
                 Key: SINGA-162
                 URL: https://issues.apache.org/jira/browse/SINGA-162
             Project: Singa
          Issue Type: Wish
            Reporter: wangwei


This ticket gives an overview of the features to be developed for V1.x.

First, we will implement a set of core abstractions,
1. Tensor, which provides basic linear algebra operations (e.g., addition) and neural net
specific operations (e.g., conv). It is a finer abstraction than Layer in V0.x, and thus could
be able to support a wider range of applications. [Autograd|https://github.com/HIPS/autograd]
would also be implemented.
2. Device, which abstract the execution and memory allocation for Tensor using different hardware/software,
including Nvidia GPU (with Cuda/Cudnn) and other GPUs using OpenCL.
3. Scheduler, which maximizes the parallelism of executions.
4. Memory manager, which manages a memory pool for a device, for garbage collection, and optimization.

Second, on top of these core abstractions, we will develop a set of modules specific for neural
networks
1. Layer for feature transformation, e.g., conv and pool
2. Model for typical models including feed-forward, RNN and energy models.
3. Updater for updating parameters on single node or in a distributed environment.

Third, some utility modules would be implemented for IO/Log/Network.



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