Habe das extrahiert:

#!/bin/bash
#git clone --recurse-submodules https://github.com/LeelaChessZero/lc0.git
#cd lc0
#git checkout master

#git clone --recurse-submodules -b dag-cup11 https://github.com/Etcaqab/lc0
#git clone --recurse-submodules -b dag-master-pr1821-pr1791 https://github.com/borg323/lc0
#git clone --recurse-submodules -b dag-master-pr1821-pr1791 https://github.com/uwuplant/lc0
#git clone --recurse-submodules -b dag-master-pr1821-pr1791 https://github.com/borg323/lc0
#git clone --recurse-submodules -b dag-update-pr1791 https://github.com/borg323/lc0
#git clone --recurse-submodules -b dag-update https://github.com/borg323/lc0
#git clone --recurse-submodules -b dag-update-test https://github.com/borg323/lc0
#git clone --recurse-submodules -b uncertainty-weighting https://github.com/Ergodice/lc0
#git clone --recurse-submodules -b Ergodice-dag-update-BT3 https://github.com/borg323/lc0
#git clone --recurse-submodules -b sufi-nps-fix https://github.com/uwuplant/lc0
#git clone --recurse-submodules -b sufi25 https://github.com/uwuplant/lc0
git clone --recurse-submodules https://github.com/Ergodice/lc0

cd lc0

read -p "Download done, press enter to continue"
CC=clang CXX=clang++ ./build.sh release -Dmalloc=tcmalloc
EXE=${PWD}/build/release/lc0

sieht gut aus!

Install backend:
If you want to use NVidia graphics cards Install CUDA and cuDNN.
If you want to use AMD graphics cards install OpenCL.
if you want OpenBLAS version Install OpenBLAS (libopenblas-dev).
Install ninja build (ninja-build), meson, and (optionally) gtest (libgtest-dev).
Go to lc0/
Run ./build.sh
lc0 will be in lc0/build/release/ directory
Unzip a neural network in the same directory as the binary.
If you want to build with a different compiler, pass the CC and CXX environment variables:

CC=clang-6.0 CXX=clang++-6.0 ./build.sh

Und das kommt bei CUDA noch dazu:

Note on installing CUDA on Ubuntu

Nvidia provides .deb packages. CUDA will be installed in /usr/local/cuda-10.0 and requires 3GB of diskspace. If your /usr/local partition doesn't have that much space left you can create a symbolic link before doing the install; for example: sudo ln -s /opt/cuda-10.0 /usr/local/cuda-10.0

The instructions given on the nvidia website tell you to finish with apt install cuda. However, this might not work (missing dependencies). In that case use apt install cuda-10-0. Afterwards you can install the meta package cuda which will cause an automatic upgrade to a newer version when that comes available (assuming you use Installer Type deb (network), if you'd want that (just cuda-10-0 will stay at version 10). If you don't know what to do, only install cuda-10-0.

cuDNN exists of two packages, the Runtime Library and the Developer Library (both a .deb package).

Before you can download the latter you need to create a (free) "developer" account with nvidia for which at least a legit email address is required (their website says: The e-mail address is not made public and will only be used if you wish to receive a new password or wish to receive certain news or notifications by e-mail.). Further they ask for a name, date of birth (not visible later on), country, organisation ("LeelaZero" if you have none), primary industry segment ("Other"/none) and which development areas you are interested in ("Deep Learning").

PS: Die Suchfunktion auf Discord mit „compiling linux“ anstoßen. Dort gibt es Fragen und Antworten.