tensorflow gpu benchmark

To avoid trouble, install all the default pathsI installed the Cuda and CUDNN versionsTensorFlow version 1.7There is a small problem here, the direct import TensorFlow has an error, I Baidu the wrong some said to install a software, but I do not want to pretend, and then input import TensorFlow as TF no errorEffective tutorials for measurementsLook at this old brother's reading line and know how much artifi

A server is loaded with multiple GPUs, and by default, when a deep learning training task is started, this task fills up almost all of the storage space for each GPU. This results in the fact that a server can only perform a single task, while the task may not require so many resources, which is tantamount to a waste of resources.The following solutions are available for this issue.First, directly set the visible GPUWrite a script that sets environmen

the profile file ( Note: If you are not using version 8.0, you need to modify the version number ):→~ Export cuda_home=/usr/local/cuda-8.0→~ Export Path=/usr/local/cuda-8.0/bin${path:+:${path}}→~ Export Ld_library_path=/usr/local/cuda-8.0/lib64${ld_library_path:+:${ld_library_path}}After modification:→~ Source/etc/profileVerify that the configuration is successful:→~ nvcc-vThe following message appears to be successful: 4. Installing the CUDNN Acceleration LibraryThis article uses the CUDA8.0,

Small white one, please give more advice, thank you.Practice proves that WIN10 + tensorflow1.6 + cuda9.1 +cudnn8.0 + python3.6 installation is not suitable (perhaps aPerson reason)Because my computer is a new computer, Win10 +python3.5 (installed with Anaconda) + cudnn8.0 +cuda9.0 Use successSome of these environment variables are not added, some are automatically added, but need to cudnn compressed all the files to paste intoThe Cuda directory.The installation process encountered a lot of probl

This machine has installed Windows system, ready to install Ubuntu dual system for TensorFlow related work, need to separate the disk in Windows for Ubuntu use1. First download the Ubuntu17.04 version of ISO2. Download Win32diskimager as installation disk burning software3. Insert a USB flash drive to burn4. Insert the USB flash drive into the computer and reboot, select USB drive5. Choose to install Ubuntu system6. Installation Type Select other opti

other dependenciessudo apt-get install python-numpy swig python-dev python-wheel?? 8. Build GPU Support (this is a compile-time hint that the GCC version is too high to downgrade http://www.cnblogs.com/alan215m/p/5906139.html)bazel build -c opt --config=cuda //tensorflow/cc:tutorials_example_trainer? If an error occurs, add--verbose_failures to run the followingbazel build -c opt --config=cuda //

I ran TensorFlow program on Ubuntu, halfway through the use of the Win+c key to the end of the program, but the GPU video memory is not released, has been in the occupied state.Using commandsNvidia-smiShown belowTwo GPU programs are in progress, in fact, gpu:0 has been stopped by the author, but the

PC configuration: GeForce GTX 1080Installing the GTX1080 DriveGo to the NVIDIA network, download the GTX1080 driver, start the search, and then download the required version. I downloaded the latest 384.130.can also be downloaded here.After the download is complete, save as a backup to refresh the new driver.Add Nvidia Source sudo add-apt-repository Ppa:graphics-drivers/ppa If the information is not considered, press ENTER directly.sudo apt-get update sudo apt-get install nvidia-384 sudo

1, install Cuda Toolkit and CUDNN (Baidu Cloud can download, version needs corresponding)2. Configure Environment variables:3, install CUDNN (need to copy some DLLs and Lib to configure)4, go to cmd, find the Anaconda3 pip path, with the following command to execute, you can uninstall the CPU version of TensorFlow, install the GPU version of the TensorFlowpip uninstall tensorflowpip install

Due to a lot of reasons I cuda9.0+cudnn7.0.5+tensorflow-gpu1.6 the environment of the machine into: cuda8.0+cudnn6.0+tensorflow-gpu1.6After the introduction of: Import TensorFlow Throws an exception when you: tensorflow:importerror:libcusolver.so.9.0 At first I was very puzzled, thought it was cuda did not uninstall clean, and re-uninstall + installation, but

The author runs TensorFlow program on Ubuntu, midway using the Win+c key to end the program, but the GPU's video memory is not released, has been in the occupied state.Using commandsWatch-n 1 Nvidia-smiShows the followingTwo GPU programs are in execution, in fact, gpu:0 has been stopped by the author, but the GPU is no