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DOC: Added TensorFlow docs

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6 merge requests!368Update prace.md to document the change from qprace to qprod as the default...,!367Update prace.md to document the change from qprace to qprod as the default...,!366Update prace.md to document the change from qprace to qprod as the default...,!323extended-acls-storage-section,!196Master,!150DOC: Added TensorFlow docs
# Machine Learning
This section overviews machine learning frameworks and libraries available on the Anselm cluster.
## TensorFlow
Load TensorFlow module:
```console
$ ml Tensorflow
```
Test module:
```console
$ ml Tensorflow
```
Read more about available versions at the [TensorFlow page](tensorflow).
# TensorFlow
TensorFlow is an open-source software library for machine intelligence.
## TensorFlow modules
Anselm provides three different TensorFlow modules:
* Tensorflow/1.1.0
* Tensorflow/1.1.0-CUDA-7.5.18-Python-3.6.1
* Tensorflow/1.1.0-CUDA-8.0.44-Python-3.6.1
### Tensorflow/1.1.0 (CPU only)
TensorFlow 1.1 build.
```console
$ ml Tensorflow/1.1.0
```
This module was built with:
* GCC/4.9.3
* Python/3.6.1
### Tensorflow/1.1.0-CUDA-7.5.18-Python-3.6.1 (GPU enabled)
TensorFlow 1.1 with GPU support.
```console
$ ml Tensorflow/1.1.0-CUDA-7.5.18-Python-3.6.1
```
This module was built with:
* GCC/4.9.3
* Python/3.6.1
* CUDA/7.5.18
* cuDNN/5.1-CUDA-7.5.18
### Tensorflow/1.1.0-CUDA-8.0.44-Python-3.6.1 (GPU enabled)
TensorFlow 1.1 with GPU support.
```console
$ ml Tensorflow/1.1.0-CUDA-8.0.44-Python-3.6.1
```
This module was built with:
* GCC/4.9.3
* Python/3.6.1
* CUDA/8.0.44
* cuDNN/5.1-CUDA-8.0.44
## TensorFlow application example
After loading one of the available TensorFlow modules, you can check the functionality running the following python script.
```python
import tensorflow as tf
c = tf.constant('Hello World!')
sess = tf.Session()
print(sess.run(c))
```
......@@ -199,7 +199,7 @@
| [spatialindex](https://libspatialindex.github.io/index.html) | The purpose of this library is to provide: * An extensible framework that will support robust spatial indexing methods. * Support for sophisticated spatial queries. Range, point location, nearest neighbor and k-nearest neighbor as well as parametric queries (defined by spatial constraints) should be easy to deploy and run. * Easy to use interfaces for inserting, deleting and updating information. |
| [SpatiaLite](https://www.gaia-gis.it/fossil/libspatialite/index) | SpatiaLite is an open source library intended to extend the SQLite core to support fully fledged Spatial SQL capabilities. |
| [tbb](http://software.intel.com/en-us/articles/intel-tbb/) | Intel Threading Building Blocks 4.0 (Intel TBB) is a widely used, award-winning C++ template library for creating reliable, portable, and scalable parallel applications. Use Intel TBB for a simple and rapid way of developing robust task-based parallel applications that scale to available processor cores, are compatible with multiple environments, and are easier to maintain. Intel TBB is the most proficient way to implement future-proof parallel applications that tap into the power and performance of multicore and manycore hardware platforms. |
| [tensorflow](http://python.org/) | Python is a programming language that lets you work more quickly and integrate your systems more effectively. |
| [tensorflow](https://www.tensorflow.org/) | Is an open-source software library for machine intelligence |
| [zlib](http://www.zlib.net/) | zlib is designed to be a free, general-purpose, legally unencumbered -- that is, not covered by any patents -- lossless data-compression library for use on virtually any computer hardware and operating system. |
## Math
......
# Machine Learning
This section overviews machine learning frameworks and libraries available on the Salomon cluster.
## TensorFlow
Load TensorFlow module:
```console
$ ml Tensorflow
```
Test module:
```console
$ ml Tensorflow
```
Read more about available versions at the [TensorFlow page](tensorflow).
# TensorFlow
TensorFlow is an open-source software library for machine intelligence.
## TensorFlow modules
Salomon provides three different TensorFlow modules:
* Tensorflow/1.1.0
* Tensorflow/1.2.0-GCC-7.1.0-2.28
* Tensorflow/1.2.0-intel-2017.05-mkl
### Tensorflow/1.1.0 (not recommended)
TensorFlow 1.1 build.
```console
$ ml Tensorflow/1.1.0
```
This module was built with:
* GCC/4.9.3
* Python/3.6.1
### Tensorflow/1.2.0-GCC-7.1.0-2.28 (default, recommended)
TensorFlow 1.2 with SIMD support. TensorFlow build taking advantage of the Salomon CPU architecture.
```console
$ ml Tensorflow/1.2.0-GCC-7.1.0-2.28
```
This module was built with:
* GCC/7.1.0-2.28
* Python/3.6.1
* protobuf/3.2.0-GCC-7.1.0-2.28-Python-3.6.1
### Tensorflow/1.2.0-intel-2017.05-mkl
TensorFlow 1.2 with MKL support.
```console
$ ml Tensorflow/1.2.0-intel-2017.05-mkl
```
This module was built with:
* icc/2017.4.196-GCC-7.1.0-2.28
* Python/3.6.1
* protobuf/3.2.0-GCC-7.1.0-2.28-Python-3.6.1
## TensorFlow application example
After loading one of the available TensorFlow modules, you can check the functionality running the following python script.
```python
import tensorflow as tf
c = tf.constant('Hello World!')
sess = tf.Session()
print(sess.run(c))
```
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