The easiest way to set the power limit permanently in ubutu with an nvidia graphics card is as follows.
#!/bin/bash sudo nvidia-smi -pm 1 sudo nvidia-smi -pl 150 -i 0
The easiest way to set the power limit permanently in ubutu with an nvidia graphics card is as follows.
#!/bin/bash sudo nvidia-smi -pm 1 sudo nvidia-smi -pl 150 -i 0
Fixes /usr/lib/libnvidia-gtk3.so.440.33.01: undefined symbol: gtk_widget_hide_on_delete
Step 1 : Check nvidia-smi for version first
Step 2: Locate nvidia-settings with same version as Step 1 at https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/ and download with wget to your system.
Step 3: Follow steps below replacing XXX with the version you downloaded.
sudo apt-get remove nvidia-modprobe nvidia-settings sudo dpkg -i nvidia-settings_XXX.deb sudo reboot now
Fixes NVIDIA-384 problem with libEGL.so.1 is not a symbolic link
sudo mv /usr/lib/nvidia-384/libEGL.so.1 /usr/lib/nvidia-384/libEGL.so.1.org sudo mv /usr/lib32/nvidia-384/libEGL.so.1 /usr/lib32/nvidia-384/libEGL.so.1.org sudo ln -s /usr/lib/nvidia-384/libEGL.so.384.90 /usr/lib/nvidia-384/libEGL.so.1 sudo ln -s /usr/lib32/nvidia-384/libEGL.so.384.90 /usr/lib32/nvidia-384/libEGL.so.1
sudo mv /usr/lib/nvidia-375/libEGL.so.1 /usr/lib/nvidia-375/libEGL.so.1.org sudo mv /usr/lib32/nvidia-375/libEGL.so.1 /usr/lib32/nvidia-375/libEGL.so.1.org sudo ln -s /usr/lib/nvidia-375/libEGL.so.375.39 /usr/lib/nvidia-375/libEGL.so.1 sudo ln -s /usr/lib32/nvidia-375/libEGL.so.375.39 /usr/lib32/nvidia-375/libEGL.so.1
This guide will teach you how to install ccminer sp-hash on Ubuntu 16.04
You must first run Install NVIDIA Driver and CUDA on Ubuntu 16.04 before proceeding.
#!/bin/bash export LD_LIBRARY_PATH=/usr/local/cuda-8.0/lib export PATH=$PATH:/usr/local/cuda-8.0/bin echo 'export PATH=/usr/local/cuda-8.0/bin:$PATH' >> ~/.bashrc mkdir sphash cd sphash git clone https://github.com/sp-hash/ccminer.git cd ccminer/ ./autogen.sh ./configure CFLAGS="-O3 -Wall -march=native" make
To buy a pre-compiled Dockerfile with this image check my selection of miner friendly Dockerfiles at https://docker.cryptoandcoffee.com
This guide will teach you how to install ccminer tpruvot on Ubuntu 16.04
You must first run Install NVIDIA Driver and CUDA on Ubuntu 16.04 before proceeding.
#!/bin/bash mkdir tpruvot cd tpruvot git clone https://github.com/tpruvot/ccminer.git cd ccminer/ export LD_LIBRARY_PATH=/usr/local/cuda-8.0/lib export PATH=$PATH:/usr/local/cuda-8.0/bin echo 'export PATH=/usr/local/cuda-8.0/bin:$PATH' >> ~/.bashrc ./autogen.sh ./configure make echo "Finished"
To buy a pre-compiled Docker container with this image compatible with NVIDIA GPU’s check my selection of miner friendly Docker containers at https://cryptoandcoffee.com
This guide will teach you how to install ccminer alexis78 on Ubuntu 16.04
You must first run Install NVIDIA Driver and CUDA on Ubuntu 16.04 before proceeding.
mkdir alexis78 cd alexis78 git clone https://github.com/alexis78/ccminer.git cd ccminer/ export LD_LIBRARY_PATH=/usr/local/cuda-8.0/lib export PATH=$PATH:/usr/local/cuda-8.0/bin ./autogen.sh ./configure make echo "Finished" exit
To buy a pre-compiled Dockerfile with this image check my selection of miner friendly Dockerfiles at https://docker.cryptoandcoffee.com
The fastest algorithm to mine on NVIDIA is by far Skein. This fork of ccminer from Klaust is definitely the fastest build of ccminer I have found to mine Skein on NVIDIA CUDA.
You must first run Install NVIDIA Driver and CUDA on Ubuntu 16.04 before proceeding.
#!/bin/bash mkdir klaust cd klaust wget https://github.com/KlausT/ccminer/archive/8.09.zip apt-get install -y unzip unzip 8.09.zip cd ccminer-8.09 apt-get install -y python3-dev echo 'add_compile_options(-std=c++11)' >> ./CMakeLists.txt ./autogen.sh ./configure make echo "Finished" exit
To buy a pre-compiled Dockerfile with this image check my selection of miner friendly Dockerfiles at https://docker.cryptoandcoffee.com
These instructions are to Install NVIDIA Driver and CUDA on Ubuntu 16.04.