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committedApr 14, 2016
[docs] install: CUDA 7+ and cuDNN v4 compatible
Latest CUDA versions are all compatible, and Caffe has been compatible with cuDNN v4 since PR BVLC#3439
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‎docs/installation.md

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Caffe has several dependencies:
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* [CUDA](https://developer.nvidia.com/cuda-zone) is required for GPU mode.
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* library version 7.0 and the latest driver version are recommended, but 6.* is fine too
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* library version 7+ and the latest driver version are recommended, but 6.* is fine too
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* 5.5, and 5.0 are compatible but considered legacy
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* [BLAS](http://en.wikipedia.org/wiki/Basic_Linear_Algebra_Subprograms) via ATLAS, MKL, or OpenBLAS.
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* [Boost](http://www.boost.org/) >= 1.55
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* [OpenCV](http://opencv.org/) >= 2.4 including 3.0
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* IO libraries: `lmdb`, `leveldb` (note: leveldb requires `snappy`)
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* cuDNN for GPU acceleration (v3)
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* cuDNN for GPU acceleration (v4)
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Pycaffe and Matcaffe interfaces have their own natural needs.
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* For Python Caffe: `Python 2.7` or `Python 3.3+`, `numpy (>= 1.7)`, boost-provided `boost.python`
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* For MATLAB Caffe: MATLAB with the `mex` compiler.
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**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.
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**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 v4; older versions are supported in older Caffe.
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**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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