MCW_CPPAMP_TORCH

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MCW_CPPAMP_TORCH

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C++ AMP backend for Torch7 NN framework

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# C++ AMP backend Implementation for Torch7 #

##Introduction: ##

This repository hosts the C++ AMP backend implementation project for  [torch7](http://torch.ch/). Torch7 framework currently has a CUDA backend support in the form of [cutorch](https://github.com/torch/cutorch) and [cunn](https://github.com/torch/cunn) packages. The goal of this project is to develop  gputorch and gpunn packages that would functionally behave as  C++ AMP counterparts for existing cutorch and cunn packages. This project mainly targets the linux platform and makes use of the linux-based C++ AMP compiler implementation hosted [here](https://bitbucket.org/multicoreware/cppamp-driver-ng/overview)

##Prerequisites: ##
* **dGPU**:  AMD firepro S9150
* **OS** : Ubuntu 14.04 LTS
* **Ubuntu Pack**: libc6-dev-i386
* **AMD APP SDK** : Ver 2.9.1 launched on 18/8/2014 from [here](http://developer.amd.com/tools-and-sdks/opencl-zone/amd-accelerated-parallel-processing-app-sdk/)
* **AMD Driver installer**: amd-driver-installer-14.301.1001-x86.x86_64

##Building and set up:    
######Need to be a super user
AMDAPPSDK on path /opt/AMDAPP (Might require to perform a rename)

(i) Torch7 install:

*  curl -sk https://raw.githubusercontent.com/torch/ezinstall/master/install-deps | bash
  
      *  curl -sk https://raw.githubusercontent.com/torch/ezinstall/master/install-luajit+torch | bash

(ii)  C++ AMP Compiler installation: Indepth details can be found [here](https://bitbucket.org/multicoreware/cppamp-driver-ng/overview)

Prepare a directory for work space.

* mkdir mcw_cppamp

* cd mcw_cppamp 
   
   * git clone https://bitbucket.org/multicoreware/cppamp-driver-ng.git src

* git checkout gmac-exp-cache-kernel (gmac-exp-cache-kernel branch is tailor made for torch7 use case)
(note that you can also use git checkout origin/gmac-exp-cache-kernel)

Create a build directory and configure using CMake.

*  mkdir mcw_cppamp/gmac_exp_build_cache

* cd mcw_cppamp/gmac_exp_build_cache

* cmake ../src -DCMAKE_BUILD_TYPE=Release (The gmac-exp-cache-kernel branch expects the AMDAPP SDK in the path /opt/AMDAPP)

Build the whole system. This will build clang and other libraries that require one time build.

* export CXXAMP_NV =1  to choose DMA implementation of clamp.

* make [-j #] world           (# is the number of parallel builds. Generally it is # of CPU cores)

* make                        (this builds llvm utilities)

Note that you might need to manually check updates from C++ AMP Compiler.
Please do the following and rebuild the Compiler if any update is available

```
 #
 # check updates from C++AMP Compiler
 cd mcw_cppamp/src
 git fetch --all
 git checkout origin/gmac-exp-cache-kernel

# check updates from C++AMP Compiler's dependency
 cd mcw_cppamp/src/compiler/tools/clang
 git fetch --all
 git checkout origin/master
```

(iii) Bolt Set up:

Bolt binaries are automatically built in (ii)

* git checkout gmac-exp-cache-kernel (Need to get back to this)

(iV) Building gputorch and gpunn:

Prior to building these packages the following environment variables need to be set using export command

* AMDAPPSDKROOT=path to AMD APP SDK (Ideally /opt/AMDAPP)
* MCWCPPAMPROOT=path to mcw_cppamp dir
* CXXAMP_NV=1 (Need to make sure this is set to use DMA)

After this the following are the steps to build gputorch and gpunn

Build Torch7 Core:

*  cd mcw_torch7_core

*  luarocks make rocks/torch-scm-1.rockspec

Build NN pack

* cd mcw_nn

* luarocks make rocks/nn-scm-1.rockspec

Build gputorch pack

* cd gputorch

* luarocks make rocks/gputorch-scm-1.rockspec

Build gpunn pack

* cd gpunn

* luarocks make rocks/gpunn-scm-1.rockspec

Testing gputorch:

* cd gputorch

* th -lgputorch -e "gputorch.test()"

If fails, run the following to get detailed messages if any,
 
```

th
 require ('gputorch')
```

Testing gpunn:

* cd gpunn

* th -lgpunn -e "nn.testgpu()"

Running FaceBook Benchmark:

Download the benchmark from [here](https://multicorewareinc.egnyte.com/dl/31EBfMX0vr)

* tar -xvf faceboook-imagenet-barebones.tar.gz

* cd imagenet-barebones

* th -i runMetaData.lua

* exit Torch prompt

* th -lgpunn -i main.lua

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