标签归档:Theano

深度学习主机环境配置: Ubuntu16.04+GeForce GTX 1080+TensorFlow

Deep Learning Specialization on Coursera

接上文《深度学习主机环境配置: Ubuntu16.04+Nvidia GTX 1080+CUDA8.0》,我们继续来安装 TensorFlow,使其支持GeForce GTX 1080显卡。

1 下载和安装cuDNN

cuDNN全称 CUDA Deep Neural Network library,是NVIDIA专门针对深度神经网络设计的一套GPU计算加速库,被广泛用于各种深度学习框架,例如Caffe, TensorFlow, Theano, Torch, CNTK等。

The NVIDIA CUDA® Deep Neural Network library (cuDNN) is a GPU-accelerated library of primitives for deep neural networks. cuDNN provides highly tuned implementations for standard routines such as forward and backward convolution, pooling, normalization, and activation layers. cuDNN is part of the NVIDIA Deep Learning SDK.

Deep learning researchers and framework developers worldwide rely on cuDNN for high-performance GPU acceleration. It allows them to focus on training neural networks and developing software applications rather than spending time on low-level GPU performance tuning. cuDNN accelerates widely used deep learning frameworks, including Caffe, TensorFlow, Theano, Torch, and CNTK. See supported frameworks for more details.

首先需要下载cuDNN,直接从Nvidia官方下载链接选择一个版本,不过下载cuDNN前同样需要登录甚至填写一个简单的调查问卷: https://developer.nvidia.com/rdp/cudnn-download,这里选择的是支持CUDA8.0的cuDNN v5版本,而支持CUDA8的5.1版本虽然显示在下载选择项里,但是提示:cuDNN 5.1 RC for CUDA 8RC will be available soon - please check back again.

屏幕快照 2016-07-17 上午11.17.39

安装cuDNN比较简单,解压后把相应的文件拷贝到对应的CUDA目录下即可:

tar -zxvf cudnn-8.0-linux-x64-v5.0-ga.tgz

cuda/include/cudnn.h
cuda/lib64/libcudnn.so
cuda/lib64/libcudnn.so.5
cuda/lib64/libcudnn.so.5.0.5
cuda/lib64/libcudnn_static.a

sudo cp cuda/include/cudnn.h /usr/local/cuda/include/
sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64/
sudo chmod a+r /usr/local/cuda/include/cudnn.h
sudo chmod a+r /usr/local/cuda/lib64/libcudnn*

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