From: Evan Shelhamer Date: Thu, 28 Aug 2014 17:55:33 +0000 (-0700) Subject: Back-merge to dev for doc fixes + cherry-picks X-Git-Url: http://review.tizen.org/git/?a=commitdiff_plain;h=c05ba59260dc9c359d900928e33c9730dc7908bf;p=platform%2Fupstream%2Fcaffe.git Back-merge to dev for doc fixes + cherry-picks Back-merge these doc fixes: clarify project origin [docs] fix citation bibtex All other changes are spurious commits from cherry-picking. --- c05ba59260dc9c359d900928e33c9730dc7908bf diff --cc docs/installation.md index b9360a9,1ac6c08..5732135 --- a/docs/installation.md +++ b/docs/installation.md @@@ -218,29 -218,8 +218,29 @@@ Be sure to set your MATLAB and Python p *Speed*: for a faster build, compile in parallel by doing `make all -j8` where 8 is the number of parallel threads for compilation (a good choice for the number of threads is the number of cores in your machine). - Now that you have installed Caffe, check out the [MNIST demo](mnist.html) and the pretrained [ImageNet example](imagenet.html). + Now that you have installed Caffe, check out the [MNIST tutorial](gathered/examples/mnist.html) and the [reference ImageNet model tutorial](gathered/examples/imagenet.html). +### Compilation using CMake (beta) + +In lieu of manually editing `Makefile.config` to tell Caffe where dependencies are located, Caffe also provides a CMake-based build system (currently in "beta"). +It requires CMake version >= 2.8.8. +The basic installation steps are as follows: + + mkdir build + cd build + cmake .. + make all + make runtest + +#### Ubuntu 12.04 + +Note that in Ubuntu 12.04, Aptitude will install version CMake 2.8.7 by default, which is not supported by Caffe's CMake build (requires at least 2.8.8). +As a workaround, if you are using Ubuntu 12.04 you can try the following steps to install (or upgrade to) CMake 2.8.9: + + sudo add-apt-repository ppa:ubuntu-sdk-team/ppa -y + sudo apt-get -y update + sudo apt-get install cmake + ## Hardware Questions **Laboratory Tested Hardware**: Berkeley Vision runs Caffe with K40s, K20s, and Titans including models at ImageNet/ILSVRC scale. We also run on GTX series cards and GPU-equipped MacBook Pros. We have not encountered any trouble in-house with devices with CUDA capability >= 3.0. All reported hardware issues thus-far have been due to GPU configuration, overheating, and the like.