How to manage different versions of CUDA, CuDNN and Nvidia Drivers?Will Nvidia Proprietary Drivers work or...

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How to manage different versions of CUDA, CuDNN and Nvidia Drivers?


Will Nvidia Proprietary Drivers work or should I use Manually installed CUDA for Ubuntu 12.04 & Blender 2.64?Installing nVidia Driver in Ubuntu 14.04 LTSNvidia drivers do not work after update on 14.04ubuntu 14.04.2 - what nvidia drivers for CUDAInstalling Nvidia drivers and CUDAStuck on 800x600 resolution on Ubuntu 14.04LTS with GeForce GTX 750 TiBlack screen on boot when any NVIDIA drivers installedProblem in installing CUDA on Intel-Nvidia hybrid graphics [Ubuntu 14.04]Which NVIDIA driver is suitable for GeForce GTX 660M?NVidia GTX660 driver not working on Ubuntu 17.10













1















I have recently update GPU in my PC, running Ubuntu 14.04



I'm trying to run some benchmarks with Caffe, but they will strongly depend on version of CUDA, CuDNN and Nvidia Drivers.



Is there any option to manage different versions CUDA, CuDNN and Nvidia Drivers?



Will different versions interfere with each other?
Is it possible to switch between versions?



Installed Nvidia drivers:



apt-cache search nvidia | grep version



nvidia-173 - NVIDIA legacy binary driver - version 173.14.39
nvidia-304 - NVIDIA legacy binary driver - version 304.131
nvidia-304-updates - NVIDIA legacy binary driver - version 304.131
nvidia-340 - NVIDIA binary driver - version 340.96
nvidia-340-updates - NVIDIA binary driver - version 340.96
nvidia-352-updates - NVIDIA binary driver - version 352.63
nvidia-352 - NVIDIA binary driver - version 352.79
nvidia-355 - NVIDIA binary driver - version 355.11
nvidia-358 - NVIDIA binary driver - version 358.16
nvidia-361 - NVIDIA binary driver - version 361.45.18
nvidia-364 - NVIDIA binary driver - version 364.19
nvidia-367 - NVIDIA binary driver - version 367.44
nvidia-370 - NVIDIA binary driver - version 370.23









share|improve this question





























    1















    I have recently update GPU in my PC, running Ubuntu 14.04



    I'm trying to run some benchmarks with Caffe, but they will strongly depend on version of CUDA, CuDNN and Nvidia Drivers.



    Is there any option to manage different versions CUDA, CuDNN and Nvidia Drivers?



    Will different versions interfere with each other?
    Is it possible to switch between versions?



    Installed Nvidia drivers:



    apt-cache search nvidia | grep version



    nvidia-173 - NVIDIA legacy binary driver - version 173.14.39
    nvidia-304 - NVIDIA legacy binary driver - version 304.131
    nvidia-304-updates - NVIDIA legacy binary driver - version 304.131
    nvidia-340 - NVIDIA binary driver - version 340.96
    nvidia-340-updates - NVIDIA binary driver - version 340.96
    nvidia-352-updates - NVIDIA binary driver - version 352.63
    nvidia-352 - NVIDIA binary driver - version 352.79
    nvidia-355 - NVIDIA binary driver - version 355.11
    nvidia-358 - NVIDIA binary driver - version 358.16
    nvidia-361 - NVIDIA binary driver - version 361.45.18
    nvidia-364 - NVIDIA binary driver - version 364.19
    nvidia-367 - NVIDIA binary driver - version 367.44
    nvidia-370 - NVIDIA binary driver - version 370.23









    share|improve this question



























      1












      1








      1


      1






      I have recently update GPU in my PC, running Ubuntu 14.04



      I'm trying to run some benchmarks with Caffe, but they will strongly depend on version of CUDA, CuDNN and Nvidia Drivers.



      Is there any option to manage different versions CUDA, CuDNN and Nvidia Drivers?



      Will different versions interfere with each other?
      Is it possible to switch between versions?



      Installed Nvidia drivers:



      apt-cache search nvidia | grep version



      nvidia-173 - NVIDIA legacy binary driver - version 173.14.39
      nvidia-304 - NVIDIA legacy binary driver - version 304.131
      nvidia-304-updates - NVIDIA legacy binary driver - version 304.131
      nvidia-340 - NVIDIA binary driver - version 340.96
      nvidia-340-updates - NVIDIA binary driver - version 340.96
      nvidia-352-updates - NVIDIA binary driver - version 352.63
      nvidia-352 - NVIDIA binary driver - version 352.79
      nvidia-355 - NVIDIA binary driver - version 355.11
      nvidia-358 - NVIDIA binary driver - version 358.16
      nvidia-361 - NVIDIA binary driver - version 361.45.18
      nvidia-364 - NVIDIA binary driver - version 364.19
      nvidia-367 - NVIDIA binary driver - version 367.44
      nvidia-370 - NVIDIA binary driver - version 370.23









      share|improve this question
















      I have recently update GPU in my PC, running Ubuntu 14.04



      I'm trying to run some benchmarks with Caffe, but they will strongly depend on version of CUDA, CuDNN and Nvidia Drivers.



      Is there any option to manage different versions CUDA, CuDNN and Nvidia Drivers?



      Will different versions interfere with each other?
      Is it possible to switch between versions?



      Installed Nvidia drivers:



      apt-cache search nvidia | grep version



      nvidia-173 - NVIDIA legacy binary driver - version 173.14.39
      nvidia-304 - NVIDIA legacy binary driver - version 304.131
      nvidia-304-updates - NVIDIA legacy binary driver - version 304.131
      nvidia-340 - NVIDIA binary driver - version 340.96
      nvidia-340-updates - NVIDIA binary driver - version 340.96
      nvidia-352-updates - NVIDIA binary driver - version 352.63
      nvidia-352 - NVIDIA binary driver - version 352.79
      nvidia-355 - NVIDIA binary driver - version 355.11
      nvidia-358 - NVIDIA binary driver - version 358.16
      nvidia-361 - NVIDIA binary driver - version 361.45.18
      nvidia-364 - NVIDIA binary driver - version 364.19
      nvidia-367 - NVIDIA binary driver - version 367.44
      nvidia-370 - NVIDIA binary driver - version 370.23






      14.04 cuda gpu gpu-drivers






      share|improve this question















      share|improve this question













      share|improve this question




      share|improve this question








      edited Aug 27 '16 at 13:29







      mrgloom

















      asked Aug 27 '16 at 13:23









      mrgloommrgloom

      3482617




      3482617






















          2 Answers
          2






          active

          oldest

          votes


















          1














          I can only answer a part of your question.



          I wrote a script to switch between multiple cuDNN versions. It currently supports v5.1, v6.0 and v7.0. You can find the script here.



          Once you complete the installation and download the cuDNN versions you want to use, you can switch between v5.1, v6.0 and v7.0 with the click of a button.



          This is what the script does:



          #!/bin/bash

          rm -f /usr/include/cudnn.h
          rm -f /usr/lib/x86_64-linux-gnu/*libcudnn*
          rm -f /usr/local/cuda-*/lib64/*libcudnn*


          cp -P packages/cudnn/include/cudnn.h /usr/include
          cp -P packages/cudnn/lib64/libcudnn* /usr/lib/x86_64-linux-gnu/
          chmod a+r /usr/lib/x86_64-linux-gnu/libcudnn*

          rm -rf packages/cudnn


          It performs the installation operations automatically for the version you need.






          share|improve this answer

































            0














            About coexistence and management of different CUDA versions, I think you can find your answer here:



            https://devtalk.nvidia.com/default/topic/493290/cuda-programming-and-performance/multiple-cuda-versions-can-they-coexist-/post/3532363/#3532363





            share








            New contributor




            Jerry Yang is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
            Check out our Code of Conduct.





















              Your Answer








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              2 Answers
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              active

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              2 Answers
              2






              active

              oldest

              votes









              active

              oldest

              votes






              active

              oldest

              votes









              1














              I can only answer a part of your question.



              I wrote a script to switch between multiple cuDNN versions. It currently supports v5.1, v6.0 and v7.0. You can find the script here.



              Once you complete the installation and download the cuDNN versions you want to use, you can switch between v5.1, v6.0 and v7.0 with the click of a button.



              This is what the script does:



              #!/bin/bash

              rm -f /usr/include/cudnn.h
              rm -f /usr/lib/x86_64-linux-gnu/*libcudnn*
              rm -f /usr/local/cuda-*/lib64/*libcudnn*


              cp -P packages/cudnn/include/cudnn.h /usr/include
              cp -P packages/cudnn/lib64/libcudnn* /usr/lib/x86_64-linux-gnu/
              chmod a+r /usr/lib/x86_64-linux-gnu/libcudnn*

              rm -rf packages/cudnn


              It performs the installation operations automatically for the version you need.






              share|improve this answer






























                1














                I can only answer a part of your question.



                I wrote a script to switch between multiple cuDNN versions. It currently supports v5.1, v6.0 and v7.0. You can find the script here.



                Once you complete the installation and download the cuDNN versions you want to use, you can switch between v5.1, v6.0 and v7.0 with the click of a button.



                This is what the script does:



                #!/bin/bash

                rm -f /usr/include/cudnn.h
                rm -f /usr/lib/x86_64-linux-gnu/*libcudnn*
                rm -f /usr/local/cuda-*/lib64/*libcudnn*


                cp -P packages/cudnn/include/cudnn.h /usr/include
                cp -P packages/cudnn/lib64/libcudnn* /usr/lib/x86_64-linux-gnu/
                chmod a+r /usr/lib/x86_64-linux-gnu/libcudnn*

                rm -rf packages/cudnn


                It performs the installation operations automatically for the version you need.






                share|improve this answer




























                  1












                  1








                  1







                  I can only answer a part of your question.



                  I wrote a script to switch between multiple cuDNN versions. It currently supports v5.1, v6.0 and v7.0. You can find the script here.



                  Once you complete the installation and download the cuDNN versions you want to use, you can switch between v5.1, v6.0 and v7.0 with the click of a button.



                  This is what the script does:



                  #!/bin/bash

                  rm -f /usr/include/cudnn.h
                  rm -f /usr/lib/x86_64-linux-gnu/*libcudnn*
                  rm -f /usr/local/cuda-*/lib64/*libcudnn*


                  cp -P packages/cudnn/include/cudnn.h /usr/include
                  cp -P packages/cudnn/lib64/libcudnn* /usr/lib/x86_64-linux-gnu/
                  chmod a+r /usr/lib/x86_64-linux-gnu/libcudnn*

                  rm -rf packages/cudnn


                  It performs the installation operations automatically for the version you need.






                  share|improve this answer















                  I can only answer a part of your question.



                  I wrote a script to switch between multiple cuDNN versions. It currently supports v5.1, v6.0 and v7.0. You can find the script here.



                  Once you complete the installation and download the cuDNN versions you want to use, you can switch between v5.1, v6.0 and v7.0 with the click of a button.



                  This is what the script does:



                  #!/bin/bash

                  rm -f /usr/include/cudnn.h
                  rm -f /usr/lib/x86_64-linux-gnu/*libcudnn*
                  rm -f /usr/local/cuda-*/lib64/*libcudnn*


                  cp -P packages/cudnn/include/cudnn.h /usr/include
                  cp -P packages/cudnn/lib64/libcudnn* /usr/lib/x86_64-linux-gnu/
                  chmod a+r /usr/lib/x86_64-linux-gnu/libcudnn*

                  rm -rf packages/cudnn


                  It performs the installation operations automatically for the version you need.







                  share|improve this answer














                  share|improve this answer



                  share|improve this answer








                  edited Sep 13 '17 at 13:05

























                  answered Sep 13 '17 at 12:42









                  dnzzcndnzzcn

                  112




                  112

























                      0














                      About coexistence and management of different CUDA versions, I think you can find your answer here:



                      https://devtalk.nvidia.com/default/topic/493290/cuda-programming-and-performance/multiple-cuda-versions-can-they-coexist-/post/3532363/#3532363





                      share








                      New contributor




                      Jerry Yang is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                      Check out our Code of Conduct.

























                        0














                        About coexistence and management of different CUDA versions, I think you can find your answer here:



                        https://devtalk.nvidia.com/default/topic/493290/cuda-programming-and-performance/multiple-cuda-versions-can-they-coexist-/post/3532363/#3532363





                        share








                        New contributor




                        Jerry Yang is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                        Check out our Code of Conduct.























                          0












                          0








                          0







                          About coexistence and management of different CUDA versions, I think you can find your answer here:



                          https://devtalk.nvidia.com/default/topic/493290/cuda-programming-and-performance/multiple-cuda-versions-can-they-coexist-/post/3532363/#3532363





                          share








                          New contributor




                          Jerry Yang is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                          Check out our Code of Conduct.










                          About coexistence and management of different CUDA versions, I think you can find your answer here:



                          https://devtalk.nvidia.com/default/topic/493290/cuda-programming-and-performance/multiple-cuda-versions-can-they-coexist-/post/3532363/#3532363






                          share








                          New contributor




                          Jerry Yang is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                          Check out our Code of Conduct.








                          share


                          share






                          New contributor




                          Jerry Yang is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                          Check out our Code of Conduct.









                          answered 6 mins ago









                          Jerry YangJerry Yang

                          1




                          1




                          New contributor




                          Jerry Yang is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                          Check out our Code of Conduct.





                          New contributor





                          Jerry Yang is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                          Check out our Code of Conduct.






                          Jerry Yang is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                          Check out our Code of Conduct.






























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