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Installation: mark cuDNN v3 compatible #3218

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Oct 19, 2015
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Installation: mark cuDNN v3 compatible #3218

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3 changes: 2 additions & 1 deletion docs/installation.md
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Expand Up @@ -30,13 +30,14 @@ Optional dependencies:

* [OpenCV](http://opencv.org/) >= 2.4 including 3.0
* IO libraries: `lmdb`, `leveldb` (note: leveldb requires `snappy`)
* cuDNN for GPU acceleration (v3)

Pycaffe and Matcaffe interfaces have their own natural needs.

* For Python Caffe: `Python 2.7` or `Python 3.3+`, `numpy (>= 1.7)`, boost-provided `boost.python`
* For MATLAB Caffe: MATLAB with the `mex` compiler.

**cuDNN Caffe**: for fastest operation Caffe is accelerated by drop-in integration of [NVIDIA cuDNN](https://developer.nvidia.com/cudnn). To speed up your Caffe models, install cuDNN then uncomment the `USE_CUDNN := 1` flag in `Makefile.config` when installing Caffe. Acceleration is automatic. For now cuDNN v1 is integrated but see [PR #1731](https://github.com/BVLC/caffe/pull/1731) for v2.
**cuDNN Caffe**: for fastest operation Caffe is accelerated by drop-in integration of [NVIDIA cuDNN](https://developer.nvidia.com/cudnn). To speed up your Caffe models, install cuDNN then uncomment the `USE_CUDNN := 1` flag in `Makefile.config` when installing Caffe. Acceleration is automatic. The current version is cuDNN v3; older versions are supported in older Caffe.

**CPU-only Caffe**: for cold-brewed CPU-only Caffe uncomment the `CPU_ONLY := 1` flag in `Makefile.config` to configure and build Caffe without CUDA. This is helpful for cloud or cluster deployment.

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