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Fix the installation doc for MKL-DNN backend #12534

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Sep 17, 2018
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Fix the installation doc for MKL-DNN backend #12534

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b25139f
fix build from souce doc for mkldnn backend
TaoLv Sep 12, 2018
547c9ba
fix doc
TaoLv Sep 12, 2018
7a019d9
Merge branch 'master' of https://github.com/apache/incubator-mxnet in…
TaoLv Sep 14, 2018
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10 changes: 5 additions & 5 deletions docs/install/build_from_source.md
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Expand Up @@ -40,7 +40,7 @@ MXNet supports multiple mathematical backends for computations on the CPU:
* [Apple Accelerate](https://developer.apple.com/documentation/accelerate)
* [ATLAS](http://math-atlas.sourceforge.net/)
* [MKL](https://software.intel.com/en-us/intel-mkl) (MKL, MKLML)
* [MKLDNN](https://github.com/intel/mkl-dnn)
* [MKL-DNN](https://github.com/intel/mkl-dnn)
* [OpenBLAS](http://www.openblas.net/)

Usage of these are covered in more detail in the [build configurations](#build-configurations) section.
Expand Down Expand Up @@ -92,13 +92,13 @@ The following lists show this order by library and `cmake` switch.

For desktop platforms (x86_64):

1. MKLDNN (submodule) | `USE_MKLDNN`
1. MKL-DNN (submodule) | `USE_MKLDNN`
2. MKL | `USE_MKL_IF_AVAILABLE`
3. MKLML (downloaded) | `USE_MKLML`
4. Apple Accelerate | `USE_APPLE_ACCELERATE_IF_AVAILABLE` | Mac only
5. OpenBLAS | `BLAS` | Options: Atlas, Open, MKL, Apple

Note: If `USE_MKL_IF_AVAILABLE` is set to False then MKLML and MKLDNN will be disabled as well for configuration
Note: If `USE_MKL_IF_AVAILABLE` is set to False then MKLML and MKL-DNN will be disabled as well for configuration
backwards compatibility.

For embedded platforms (all other and if cross compiled):
Expand Down Expand Up @@ -129,8 +129,8 @@ It has following flavors:
<!-- [Removed until #11148 is merged.] This is the most effective option since it can be downloaded and installed automatically
by the cmake script (see cmake/DownloadMKLML.cmake).-->

* MKLDNN is a separate open-source library, it can be used separately from MKL or MKLML. It is
shipped as a subrepo with MXNet source code (see 3rdparty/mkldnn or the [mkl-dnn project](https://github.com/intel/mkl-dnn))
* MKL-DNN is a separate open-source library, it can be used separately from MKL or MKLML. It is
shipped as a subrepo with MXNet source code (see 3rdparty/mkldnn or the [MKL-DNN project](https://github.com/intel/mkl-dnn))

Since the full MKL library is almost always faster than any other BLAS library it's turned on by default,
however it needs to be downloaded and installed manually before doing `cmake` configuration.
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10 changes: 9 additions & 1 deletion docs/install/ubuntu_setup.md
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Expand Up @@ -70,7 +70,7 @@ pip install mxnet-cu92mkl

Alternatively, you can use the table below to select the package that suits your purpose.

| MXNet Version | Basic | CUDA | MKL | CUDA/MKL |
| MXNet Version | Basic | CUDA | MKL-DNN | CUDA/MKL-DNN |
|-|-|-|-|-|
| Latest | mxnet | mxnet-cu92 | mxnet-mkl | mxnet-cu92mkl |

Expand Down Expand Up @@ -167,6 +167,14 @@ If building on CPU and using OpenBLAS:
make -j $(nproc) USE_OPENCV=1 USE_BLAS=openblas
```

If building on CPU and using MKL and MKL-DNN (make sure MKL is installed according to [Math Library Selection](build_from_source.html#math-library-selection) and [MKL-DNN README](https://github.com/apache/incubator-mxnet/blob/master/MKLDNN_README.md)):

```bash
git clone --recursive https://github.com/apache/incubator-mxnet.git
cd mxnet
make -j $(nproc) USE_OPENCV=1 USE_BLAS=mkl USE_MKLDNN=1
```

If building on GPU and you want OpenCV and OpenBLAS (make sure you have installed the [CUDA dependencies first](#cuda-dependencies)):

```bash
Expand Down