From b265134710d78db4007471ccbe376c2c4221441a Mon Sep 17 00:00:00 2001 From: Evan Shelhamer Date: Wed, 13 Apr 2016 16:40:30 -0700 Subject: [PATCH] [docs] install: CUDA 7+ and cuDNN v4 compatible Latest CUDA versions are all compatible, and Caffe has been compatible with cuDNN v4 since PR #3439 --- docs/installation.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/installation.md b/docs/installation.md index 893164584d9..e6c6886df52 100644 --- a/docs/installation.md +++ b/docs/installation.md @@ -20,7 +20,7 @@ When updating Caffe, it's best to `make clean` before re-compiling. Caffe has several dependencies: * [CUDA](https://developer.nvidia.com/cuda-zone) is required for GPU mode. - * library version 7.0 and the latest driver version are recommended, but 6.* is fine too + * library version 7+ and the latest driver version are recommended, but 6.* is fine too * 5.5, and 5.0 are compatible but considered legacy * [BLAS](http://en.wikipedia.org/wiki/Basic_Linear_Algebra_Subprograms) via ATLAS, MKL, or OpenBLAS. * [Boost](http://www.boost.org/) >= 1.55 @@ -30,14 +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) +* cuDNN for GPU acceleration (v4) 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. The current version is cuDNN v3; older versions are supported in older Caffe. +**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. **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.