Getting CUDA 8.0 to work on Ubuntu 16.04, NVIDIA driver issue
I've spent a couple of days on this and am at my wit's end as to how to move forward.
I have an ASUS Zenbook UX303UB with Windows 10 and Ubuntu 16.04 Dual boot. It has an NVIDIA GeForce 940M dedicated GPU with 2GB memory. I use Ubuntu primarily for programming. I want to play around with some deep learning tools like tensorflow and theano, for which I first need CUDA to work. Only CUDA 8.0rc appears to work with Ubuntu 16.04 officially.
First, I went to the NVIDIA website and downloaded the CUDA 8.0 runfile. I followed their instructions to install and did so in TTY1, including blacklisting noveau and adding
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}}
to the end of the .bashrc file.
When I try the test example that NVIDIA provides,
$ cd NVIDIA_CUDA-8.0_Samples/5_Simulations/nbody
$ make
my output is:
>>> WARNING - libGLU.so not found, refer to CUDA Getting Started Guide for how to find and install them. <<<
>>> WARNING - gl.h not found, refer to CUDA Getting Started Guide for how to find and install them. <<<
>>> WARNING - glu.h not found, refer to CUDA Getting Started Guide for how to find and install them. <<<
[@] /usr/local/cuda-8.0/bin/nvcc -ccbin g++ -I../../common/inc -m64 -ftz=true -gencode arch=compute_20,code=sm_20 -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_60,code=compute_60 -o bodysystemcuda.o -c bodysystemcuda.cu
[@] /usr/local/cuda-8.0/bin/nvcc -ccbin g++ -I../../common/inc -m64 -ftz=true -gencode arch=compute_20,code=sm_20 -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_60,code=compute_60 -o nbody.o -c nbody.cpp
[@] /usr/local/cuda-8.0/bin/nvcc -ccbin g++ -I../../common/inc -m64 -ftz=true -gencode arch=compute_20,code=sm_20 -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_60,code=compute_60 -o render_particles.o -c render_particles.cpp
[@] /usr/local/cuda-8.0/bin/nvcc -ccbin g++ -m64 -gencode arch=compute_20,code=sm_20 -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_60,code=compute_60 -o nbody bodysystemcuda.o nbody.o render_particles.o -L/usr/lib/nvidia-361 -lGL -lGLU -lX11 -lglut
[@] mkdir -p ../../bin/x86_64/linux/release
[@] cp nbody ../../bin/x86_64/linux/release
when I then do
$ ./nbody -benchmark -numbodies=256000 -device=0
I get the message
bash: ./nbody: No such file or directory
In the diagnosis process, I realized 2 things:
1) nvidia-smi
doesn't seem to work (nvidia-smi: command not found
)
2) When I do cat /proc/driver/nvidia/version
I get cat: /proc/driver/nvidia/version: No such file or directory
I then decided perhaps there is some trouble with the NVIDIA driver. So I followed the instructions on
Issues with Nvidia graphics driver and CUDA after apt-get upgrade
Basically, to purge all nvidia drivers, turn off lightdm and enter runlevel3, and install the NVIDIA driver runfile from NVIDIA's website.
However, there is an installation error and it aborts.
I then reboot and purge all nvidia drivers and do a sudo apt-get install nvidia-367
I'm back to square one now. Additional diagnostic information as follows:
$ sudo nvidia-modprobe
sudo: nvidia-modprobe: command not found
$ uname -r
4.4.0-36-generic
$ dpkg -l | grep ii | grep -i linux-headers
ii linux-headers-4.4.0-31 4.4.0-31.50 all Header files related to Linux kernel version 4.4.0
ii linux-headers-4.4.0-31-generic 4.4.0-31.50 amd64 Linux kernel headers for version 4.4.0 on 64 bit x86 SMP
ii linux-headers-4.4.0-34 4.4.0-34.53 all Header files related to Linux kernel version 4.4.0
ii linux-headers-4.4.0-34-generic 4.4.0-34.53 amd64 Linux kernel headers for version 4.4.0 on 64 bit x86 SMP
ii linux-headers-4.4.0-36 4.4.0-36.55 all Header files related to Linux kernel version 4.4.0
ii linux-headers-4.4.0-36-generic 4.4.0-36.55 amd64 Linux kernel headers for version 4.4.0 on 64 bit x86 SMP
ii linux-headers-generic 4.4.0.36.38 amd64 Generic Linux kernel headers
$ dpkg -l | grep -i nvidia
ii bbswitch-dkms 0.8-3ubuntu1 amd64 Interface for toggling the power on NVIDIA Optimus video cards
ii libcuda1-367 367.44-0ubuntu0~gpu16.04.1 amd64 NVIDIA CUDA runtime library
ii nvidia-367 367.44-0ubuntu0~gpu16.04.1 amd64 NVIDIA binary driver - version 367.44
ii nvidia-opencl-icd-367 367.44-0ubuntu0~gpu16.04.1 amd64 NVIDIA OpenCL ICD
ii nvidia-prime 0.8.2 amd64 Tools to enable NVIDIA's Prime
ii nvidia-settings 370.23-0ubuntu0~gpu16.04.1 amd64 Tool for configuring the NVIDIA graphics driver
$ nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2016 NVIDIA Corporation
Built on Wed_May__4_21:01:56_CDT_2016
Cuda compilation tools, release 8.0, V8.0.26
Any help would be much appreciated, as I have come very close to breaking ubuntu a bunch of times!!
16.04 cuda nvidia-geforce
bumped to the homepage by Community♦ 8 hours ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
I've spent a couple of days on this and am at my wit's end as to how to move forward.
I have an ASUS Zenbook UX303UB with Windows 10 and Ubuntu 16.04 Dual boot. It has an NVIDIA GeForce 940M dedicated GPU with 2GB memory. I use Ubuntu primarily for programming. I want to play around with some deep learning tools like tensorflow and theano, for which I first need CUDA to work. Only CUDA 8.0rc appears to work with Ubuntu 16.04 officially.
First, I went to the NVIDIA website and downloaded the CUDA 8.0 runfile. I followed their instructions to install and did so in TTY1, including blacklisting noveau and adding
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}}
to the end of the .bashrc file.
When I try the test example that NVIDIA provides,
$ cd NVIDIA_CUDA-8.0_Samples/5_Simulations/nbody
$ make
my output is:
>>> WARNING - libGLU.so not found, refer to CUDA Getting Started Guide for how to find and install them. <<<
>>> WARNING - gl.h not found, refer to CUDA Getting Started Guide for how to find and install them. <<<
>>> WARNING - glu.h not found, refer to CUDA Getting Started Guide for how to find and install them. <<<
[@] /usr/local/cuda-8.0/bin/nvcc -ccbin g++ -I../../common/inc -m64 -ftz=true -gencode arch=compute_20,code=sm_20 -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_60,code=compute_60 -o bodysystemcuda.o -c bodysystemcuda.cu
[@] /usr/local/cuda-8.0/bin/nvcc -ccbin g++ -I../../common/inc -m64 -ftz=true -gencode arch=compute_20,code=sm_20 -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_60,code=compute_60 -o nbody.o -c nbody.cpp
[@] /usr/local/cuda-8.0/bin/nvcc -ccbin g++ -I../../common/inc -m64 -ftz=true -gencode arch=compute_20,code=sm_20 -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_60,code=compute_60 -o render_particles.o -c render_particles.cpp
[@] /usr/local/cuda-8.0/bin/nvcc -ccbin g++ -m64 -gencode arch=compute_20,code=sm_20 -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_60,code=compute_60 -o nbody bodysystemcuda.o nbody.o render_particles.o -L/usr/lib/nvidia-361 -lGL -lGLU -lX11 -lglut
[@] mkdir -p ../../bin/x86_64/linux/release
[@] cp nbody ../../bin/x86_64/linux/release
when I then do
$ ./nbody -benchmark -numbodies=256000 -device=0
I get the message
bash: ./nbody: No such file or directory
In the diagnosis process, I realized 2 things:
1) nvidia-smi
doesn't seem to work (nvidia-smi: command not found
)
2) When I do cat /proc/driver/nvidia/version
I get cat: /proc/driver/nvidia/version: No such file or directory
I then decided perhaps there is some trouble with the NVIDIA driver. So I followed the instructions on
Issues with Nvidia graphics driver and CUDA after apt-get upgrade
Basically, to purge all nvidia drivers, turn off lightdm and enter runlevel3, and install the NVIDIA driver runfile from NVIDIA's website.
However, there is an installation error and it aborts.
I then reboot and purge all nvidia drivers and do a sudo apt-get install nvidia-367
I'm back to square one now. Additional diagnostic information as follows:
$ sudo nvidia-modprobe
sudo: nvidia-modprobe: command not found
$ uname -r
4.4.0-36-generic
$ dpkg -l | grep ii | grep -i linux-headers
ii linux-headers-4.4.0-31 4.4.0-31.50 all Header files related to Linux kernel version 4.4.0
ii linux-headers-4.4.0-31-generic 4.4.0-31.50 amd64 Linux kernel headers for version 4.4.0 on 64 bit x86 SMP
ii linux-headers-4.4.0-34 4.4.0-34.53 all Header files related to Linux kernel version 4.4.0
ii linux-headers-4.4.0-34-generic 4.4.0-34.53 amd64 Linux kernel headers for version 4.4.0 on 64 bit x86 SMP
ii linux-headers-4.4.0-36 4.4.0-36.55 all Header files related to Linux kernel version 4.4.0
ii linux-headers-4.4.0-36-generic 4.4.0-36.55 amd64 Linux kernel headers for version 4.4.0 on 64 bit x86 SMP
ii linux-headers-generic 4.4.0.36.38 amd64 Generic Linux kernel headers
$ dpkg -l | grep -i nvidia
ii bbswitch-dkms 0.8-3ubuntu1 amd64 Interface for toggling the power on NVIDIA Optimus video cards
ii libcuda1-367 367.44-0ubuntu0~gpu16.04.1 amd64 NVIDIA CUDA runtime library
ii nvidia-367 367.44-0ubuntu0~gpu16.04.1 amd64 NVIDIA binary driver - version 367.44
ii nvidia-opencl-icd-367 367.44-0ubuntu0~gpu16.04.1 amd64 NVIDIA OpenCL ICD
ii nvidia-prime 0.8.2 amd64 Tools to enable NVIDIA's Prime
ii nvidia-settings 370.23-0ubuntu0~gpu16.04.1 amd64 Tool for configuring the NVIDIA graphics driver
$ nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2016 NVIDIA Corporation
Built on Wed_May__4_21:01:56_CDT_2016
Cuda compilation tools, release 8.0, V8.0.26
Any help would be much appreciated, as I have come very close to breaking ubuntu a bunch of times!!
16.04 cuda nvidia-geforce
bumped to the homepage by Community♦ 8 hours ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
This blog may help: pugetsystems.com/labs/hpc/… I am still reviewing, and don't agree with all of the methods described. Will post answer here, when I have had time test this approach.
– david6
Sep 6 '16 at 8:49
add a comment |
I've spent a couple of days on this and am at my wit's end as to how to move forward.
I have an ASUS Zenbook UX303UB with Windows 10 and Ubuntu 16.04 Dual boot. It has an NVIDIA GeForce 940M dedicated GPU with 2GB memory. I use Ubuntu primarily for programming. I want to play around with some deep learning tools like tensorflow and theano, for which I first need CUDA to work. Only CUDA 8.0rc appears to work with Ubuntu 16.04 officially.
First, I went to the NVIDIA website and downloaded the CUDA 8.0 runfile. I followed their instructions to install and did so in TTY1, including blacklisting noveau and adding
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}}
to the end of the .bashrc file.
When I try the test example that NVIDIA provides,
$ cd NVIDIA_CUDA-8.0_Samples/5_Simulations/nbody
$ make
my output is:
>>> WARNING - libGLU.so not found, refer to CUDA Getting Started Guide for how to find and install them. <<<
>>> WARNING - gl.h not found, refer to CUDA Getting Started Guide for how to find and install them. <<<
>>> WARNING - glu.h not found, refer to CUDA Getting Started Guide for how to find and install them. <<<
[@] /usr/local/cuda-8.0/bin/nvcc -ccbin g++ -I../../common/inc -m64 -ftz=true -gencode arch=compute_20,code=sm_20 -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_60,code=compute_60 -o bodysystemcuda.o -c bodysystemcuda.cu
[@] /usr/local/cuda-8.0/bin/nvcc -ccbin g++ -I../../common/inc -m64 -ftz=true -gencode arch=compute_20,code=sm_20 -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_60,code=compute_60 -o nbody.o -c nbody.cpp
[@] /usr/local/cuda-8.0/bin/nvcc -ccbin g++ -I../../common/inc -m64 -ftz=true -gencode arch=compute_20,code=sm_20 -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_60,code=compute_60 -o render_particles.o -c render_particles.cpp
[@] /usr/local/cuda-8.0/bin/nvcc -ccbin g++ -m64 -gencode arch=compute_20,code=sm_20 -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_60,code=compute_60 -o nbody bodysystemcuda.o nbody.o render_particles.o -L/usr/lib/nvidia-361 -lGL -lGLU -lX11 -lglut
[@] mkdir -p ../../bin/x86_64/linux/release
[@] cp nbody ../../bin/x86_64/linux/release
when I then do
$ ./nbody -benchmark -numbodies=256000 -device=0
I get the message
bash: ./nbody: No such file or directory
In the diagnosis process, I realized 2 things:
1) nvidia-smi
doesn't seem to work (nvidia-smi: command not found
)
2) When I do cat /proc/driver/nvidia/version
I get cat: /proc/driver/nvidia/version: No such file or directory
I then decided perhaps there is some trouble with the NVIDIA driver. So I followed the instructions on
Issues with Nvidia graphics driver and CUDA after apt-get upgrade
Basically, to purge all nvidia drivers, turn off lightdm and enter runlevel3, and install the NVIDIA driver runfile from NVIDIA's website.
However, there is an installation error and it aborts.
I then reboot and purge all nvidia drivers and do a sudo apt-get install nvidia-367
I'm back to square one now. Additional diagnostic information as follows:
$ sudo nvidia-modprobe
sudo: nvidia-modprobe: command not found
$ uname -r
4.4.0-36-generic
$ dpkg -l | grep ii | grep -i linux-headers
ii linux-headers-4.4.0-31 4.4.0-31.50 all Header files related to Linux kernel version 4.4.0
ii linux-headers-4.4.0-31-generic 4.4.0-31.50 amd64 Linux kernel headers for version 4.4.0 on 64 bit x86 SMP
ii linux-headers-4.4.0-34 4.4.0-34.53 all Header files related to Linux kernel version 4.4.0
ii linux-headers-4.4.0-34-generic 4.4.0-34.53 amd64 Linux kernel headers for version 4.4.0 on 64 bit x86 SMP
ii linux-headers-4.4.0-36 4.4.0-36.55 all Header files related to Linux kernel version 4.4.0
ii linux-headers-4.4.0-36-generic 4.4.0-36.55 amd64 Linux kernel headers for version 4.4.0 on 64 bit x86 SMP
ii linux-headers-generic 4.4.0.36.38 amd64 Generic Linux kernel headers
$ dpkg -l | grep -i nvidia
ii bbswitch-dkms 0.8-3ubuntu1 amd64 Interface for toggling the power on NVIDIA Optimus video cards
ii libcuda1-367 367.44-0ubuntu0~gpu16.04.1 amd64 NVIDIA CUDA runtime library
ii nvidia-367 367.44-0ubuntu0~gpu16.04.1 amd64 NVIDIA binary driver - version 367.44
ii nvidia-opencl-icd-367 367.44-0ubuntu0~gpu16.04.1 amd64 NVIDIA OpenCL ICD
ii nvidia-prime 0.8.2 amd64 Tools to enable NVIDIA's Prime
ii nvidia-settings 370.23-0ubuntu0~gpu16.04.1 amd64 Tool for configuring the NVIDIA graphics driver
$ nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2016 NVIDIA Corporation
Built on Wed_May__4_21:01:56_CDT_2016
Cuda compilation tools, release 8.0, V8.0.26
Any help would be much appreciated, as I have come very close to breaking ubuntu a bunch of times!!
16.04 cuda nvidia-geforce
I've spent a couple of days on this and am at my wit's end as to how to move forward.
I have an ASUS Zenbook UX303UB with Windows 10 and Ubuntu 16.04 Dual boot. It has an NVIDIA GeForce 940M dedicated GPU with 2GB memory. I use Ubuntu primarily for programming. I want to play around with some deep learning tools like tensorflow and theano, for which I first need CUDA to work. Only CUDA 8.0rc appears to work with Ubuntu 16.04 officially.
First, I went to the NVIDIA website and downloaded the CUDA 8.0 runfile. I followed their instructions to install and did so in TTY1, including blacklisting noveau and adding
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}}
to the end of the .bashrc file.
When I try the test example that NVIDIA provides,
$ cd NVIDIA_CUDA-8.0_Samples/5_Simulations/nbody
$ make
my output is:
>>> WARNING - libGLU.so not found, refer to CUDA Getting Started Guide for how to find and install them. <<<
>>> WARNING - gl.h not found, refer to CUDA Getting Started Guide for how to find and install them. <<<
>>> WARNING - glu.h not found, refer to CUDA Getting Started Guide for how to find and install them. <<<
[@] /usr/local/cuda-8.0/bin/nvcc -ccbin g++ -I../../common/inc -m64 -ftz=true -gencode arch=compute_20,code=sm_20 -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_60,code=compute_60 -o bodysystemcuda.o -c bodysystemcuda.cu
[@] /usr/local/cuda-8.0/bin/nvcc -ccbin g++ -I../../common/inc -m64 -ftz=true -gencode arch=compute_20,code=sm_20 -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_60,code=compute_60 -o nbody.o -c nbody.cpp
[@] /usr/local/cuda-8.0/bin/nvcc -ccbin g++ -I../../common/inc -m64 -ftz=true -gencode arch=compute_20,code=sm_20 -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_60,code=compute_60 -o render_particles.o -c render_particles.cpp
[@] /usr/local/cuda-8.0/bin/nvcc -ccbin g++ -m64 -gencode arch=compute_20,code=sm_20 -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_60,code=compute_60 -o nbody bodysystemcuda.o nbody.o render_particles.o -L/usr/lib/nvidia-361 -lGL -lGLU -lX11 -lglut
[@] mkdir -p ../../bin/x86_64/linux/release
[@] cp nbody ../../bin/x86_64/linux/release
when I then do
$ ./nbody -benchmark -numbodies=256000 -device=0
I get the message
bash: ./nbody: No such file or directory
In the diagnosis process, I realized 2 things:
1) nvidia-smi
doesn't seem to work (nvidia-smi: command not found
)
2) When I do cat /proc/driver/nvidia/version
I get cat: /proc/driver/nvidia/version: No such file or directory
I then decided perhaps there is some trouble with the NVIDIA driver. So I followed the instructions on
Issues with Nvidia graphics driver and CUDA after apt-get upgrade
Basically, to purge all nvidia drivers, turn off lightdm and enter runlevel3, and install the NVIDIA driver runfile from NVIDIA's website.
However, there is an installation error and it aborts.
I then reboot and purge all nvidia drivers and do a sudo apt-get install nvidia-367
I'm back to square one now. Additional diagnostic information as follows:
$ sudo nvidia-modprobe
sudo: nvidia-modprobe: command not found
$ uname -r
4.4.0-36-generic
$ dpkg -l | grep ii | grep -i linux-headers
ii linux-headers-4.4.0-31 4.4.0-31.50 all Header files related to Linux kernel version 4.4.0
ii linux-headers-4.4.0-31-generic 4.4.0-31.50 amd64 Linux kernel headers for version 4.4.0 on 64 bit x86 SMP
ii linux-headers-4.4.0-34 4.4.0-34.53 all Header files related to Linux kernel version 4.4.0
ii linux-headers-4.4.0-34-generic 4.4.0-34.53 amd64 Linux kernel headers for version 4.4.0 on 64 bit x86 SMP
ii linux-headers-4.4.0-36 4.4.0-36.55 all Header files related to Linux kernel version 4.4.0
ii linux-headers-4.4.0-36-generic 4.4.0-36.55 amd64 Linux kernel headers for version 4.4.0 on 64 bit x86 SMP
ii linux-headers-generic 4.4.0.36.38 amd64 Generic Linux kernel headers
$ dpkg -l | grep -i nvidia
ii bbswitch-dkms 0.8-3ubuntu1 amd64 Interface for toggling the power on NVIDIA Optimus video cards
ii libcuda1-367 367.44-0ubuntu0~gpu16.04.1 amd64 NVIDIA CUDA runtime library
ii nvidia-367 367.44-0ubuntu0~gpu16.04.1 amd64 NVIDIA binary driver - version 367.44
ii nvidia-opencl-icd-367 367.44-0ubuntu0~gpu16.04.1 amd64 NVIDIA OpenCL ICD
ii nvidia-prime 0.8.2 amd64 Tools to enable NVIDIA's Prime
ii nvidia-settings 370.23-0ubuntu0~gpu16.04.1 amd64 Tool for configuring the NVIDIA graphics driver
$ nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2016 NVIDIA Corporation
Built on Wed_May__4_21:01:56_CDT_2016
Cuda compilation tools, release 8.0, V8.0.26
Any help would be much appreciated, as I have come very close to breaking ubuntu a bunch of times!!
16.04 cuda nvidia-geforce
16.04 cuda nvidia-geforce
edited Apr 13 '17 at 12:24
Community♦
1
1
asked Sep 5 '16 at 3:35
mwolverine
3112
3112
bumped to the homepage by Community♦ 8 hours ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
bumped to the homepage by Community♦ 8 hours ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
This blog may help: pugetsystems.com/labs/hpc/… I am still reviewing, and don't agree with all of the methods described. Will post answer here, when I have had time test this approach.
– david6
Sep 6 '16 at 8:49
add a comment |
This blog may help: pugetsystems.com/labs/hpc/… I am still reviewing, and don't agree with all of the methods described. Will post answer here, when I have had time test this approach.
– david6
Sep 6 '16 at 8:49
This blog may help: pugetsystems.com/labs/hpc/… I am still reviewing, and don't agree with all of the methods described. Will post answer here, when I have had time test this approach.
– david6
Sep 6 '16 at 8:49
This blog may help: pugetsystems.com/labs/hpc/… I am still reviewing, and don't agree with all of the methods described. Will post answer here, when I have had time test this approach.
– david6
Sep 6 '16 at 8:49
add a comment |
1 Answer
1
active
oldest
votes
I solved it by following this tutorial: http://kislayabhi.github.io/Installing_CUDA_with_Ubuntu/
Follow it loosely, i.e. download and install the lastest driver from nvidia's website instead of downloading and installing nvidia-367 which the tutorial recommends.
5
Please add the important points from the post and add your modifications so in case the link changes we will have a working copy.
– George Udosen
Mar 1 '17 at 13:19
add a comment |
Your Answer
StackExchange.ready(function() {
var channelOptions = {
tags: "".split(" "),
id: "89"
};
initTagRenderer("".split(" "), "".split(" "), channelOptions);
StackExchange.using("externalEditor", function() {
// Have to fire editor after snippets, if snippets enabled
if (StackExchange.settings.snippets.snippetsEnabled) {
StackExchange.using("snippets", function() {
createEditor();
});
}
else {
createEditor();
}
});
function createEditor() {
StackExchange.prepareEditor({
heartbeatType: 'answer',
autoActivateHeartbeat: false,
convertImagesToLinks: true,
noModals: true,
showLowRepImageUploadWarning: true,
reputationToPostImages: 10,
bindNavPrevention: true,
postfix: "",
imageUploader: {
brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
allowUrls: true
},
onDemand: true,
discardSelector: ".discard-answer"
,immediatelyShowMarkdownHelp:true
});
}
});
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2faskubuntu.com%2fquestions%2f821065%2fgetting-cuda-8-0-to-work-on-ubuntu-16-04-nvidia-driver-issue%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
I solved it by following this tutorial: http://kislayabhi.github.io/Installing_CUDA_with_Ubuntu/
Follow it loosely, i.e. download and install the lastest driver from nvidia's website instead of downloading and installing nvidia-367 which the tutorial recommends.
5
Please add the important points from the post and add your modifications so in case the link changes we will have a working copy.
– George Udosen
Mar 1 '17 at 13:19
add a comment |
I solved it by following this tutorial: http://kislayabhi.github.io/Installing_CUDA_with_Ubuntu/
Follow it loosely, i.e. download and install the lastest driver from nvidia's website instead of downloading and installing nvidia-367 which the tutorial recommends.
5
Please add the important points from the post and add your modifications so in case the link changes we will have a working copy.
– George Udosen
Mar 1 '17 at 13:19
add a comment |
I solved it by following this tutorial: http://kislayabhi.github.io/Installing_CUDA_with_Ubuntu/
Follow it loosely, i.e. download and install the lastest driver from nvidia's website instead of downloading and installing nvidia-367 which the tutorial recommends.
I solved it by following this tutorial: http://kislayabhi.github.io/Installing_CUDA_with_Ubuntu/
Follow it loosely, i.e. download and install the lastest driver from nvidia's website instead of downloading and installing nvidia-367 which the tutorial recommends.
answered Mar 1 '17 at 11:14
E. Stoelinga
11
11
5
Please add the important points from the post and add your modifications so in case the link changes we will have a working copy.
– George Udosen
Mar 1 '17 at 13:19
add a comment |
5
Please add the important points from the post and add your modifications so in case the link changes we will have a working copy.
– George Udosen
Mar 1 '17 at 13:19
5
5
Please add the important points from the post and add your modifications so in case the link changes we will have a working copy.
– George Udosen
Mar 1 '17 at 13:19
Please add the important points from the post and add your modifications so in case the link changes we will have a working copy.
– George Udosen
Mar 1 '17 at 13:19
add a comment |
Thanks for contributing an answer to Ask Ubuntu!
- Please be sure to answer the question. Provide details and share your research!
But avoid …
- Asking for help, clarification, or responding to other answers.
- Making statements based on opinion; back them up with references or personal experience.
To learn more, see our tips on writing great answers.
Some of your past answers have not been well-received, and you're in danger of being blocked from answering.
Please pay close attention to the following guidance:
- Please be sure to answer the question. Provide details and share your research!
But avoid …
- Asking for help, clarification, or responding to other answers.
- Making statements based on opinion; back them up with references or personal experience.
To learn more, see our tips on writing great answers.
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2faskubuntu.com%2fquestions%2f821065%2fgetting-cuda-8-0-to-work-on-ubuntu-16-04-nvidia-driver-issue%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
This blog may help: pugetsystems.com/labs/hpc/… I am still reviewing, and don't agree with all of the methods described. Will post answer here, when I have had time test this approach.
– david6
Sep 6 '16 at 8:49