CUDA-13.0.0

Introduction to CUDA

The CUDA proprietary toolkit provides tools for running code on NVIDIA GPUs. This is otherwise known as hardware acceleration.

[Viktig]

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The NVIDIA driver version listed in the runfile name is the minimum NVIDIA driver version required. You must install an older version of CUDA if you cannot install a newer driver version.

[Notat]

Notat

The download size is over 5G, so you should consider if and when you will want to download this runfile. For this reason, it is not recommended to download it when using limited hotspot data. Its size can largely be attributed to containing compilers as well as the NVIDIA driver. The driver only accounts for 10% of the runfile's size.

CUDA Dependencies

Required

NVIDIA

Recommended

Optional

GDB and GLU

Installation of CUDA

First create the installation directory and symlink as the root user:

mkdir -pv /opt/cuda-13.0.0 &&
ln -sfv cuda-13.0.0 /opt/cuda
[Notat]

Notat

Når du installerer flere pakker i et skript, må installasjonen gjøres som root bruker. Det finnes tre generelle alternativer som kan brukes til å gjøre dette:

  1. Kjør hele skriptet som root bruker (ikke anbefalt).

  2. Bruk sudo kommandoen fra sudo pakken.

  3. Use su -c "command arguments" (anførselstegn kreves) som vil be om root passordet for hver iterasjon av løkken.

En måte å håndtere denne situasjonen på er å lage en kort bash funksjon som automatisk velger riktig metode. Når kommandoen er satt i miljøet, trenger den ikke å settes på nytt.

as_root()
{
  if   [ $EUID = 0 ];        then $*
  elif [ -x /usr/bin/sudo ]; then sudo $*
  else                            su -c \\"$*\\"
  fi
}

export -f as_root

Start a subshell that will exit on an error:

bash -e

Install CUDA by running the following commands:

sh cuda_13.0.0_580.65.06_linux.run     \
  --target cuda_13.0.0_580.65.06_linux \
  --noexec
pushd cuda_13.0.0_580.65.06_linux/builds
  rm -rf cuda_nsight cuda_sanitizer_api nsight_{compute,systems}
  rm -rvf bin integration NVIDIA*.run
  as_root cp version.json /opt/cuda-13.0.0
  as_root cp EULA.txt     /opt/cuda-13.0.0
  rm version.json EULA.txt
  as_root mkdir -p /opt/cuda-13.0.0/bin
  for lib in *; do
    as_root cp -vR $lib/* /opt/cuda-13.0.0
    rm -rf $lib
  done
  as_root ln -svf lib64 /opt/cuda-13.0.0/lib
  for mf in $(find /opt/cuda-13.0.0 -name Makefile); do
    as_root sed -i "s|/usr/local/cuda|/opt/cuda-13.0.0|g" "$mf"
  done
popd
rm -rf cuda_13.0.0_580.65.06_linux
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Notat

The above instructions extract the runfile and installs components manually. In the past, this was not needed. However, once cuda_installer failed to load as it relied on an older libxml2 ABI, this process became the preferred solution. It will remain as it allows for more control, despite being a more complicated solution.

Now exit the subshell process:

exit

As the root user, allow the use of new compilers:

sed -e "/.*unsupported GNU version.*/d" \
    -e "/.*unsupported clang version.*/d" \
    -i /opt/cuda-13.0.0/targets/x86_64-linux/include/crt/host_config.h
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This technically is not supported and there may be compilation errors in other packages as a result. However, it's a better compromise than installing older compilers just for one package. This package is still being developed but takes a long time to adapt to newer software.

Command Explanations

--target: This parameter specifies the extraction directory.

--noexec: This parameter does ensures the toolkit does not get triggered for installation.

Configuring CUDA

Ensure the libraries are cached as the root user:

cat > /etc/ld.so.conf.d/cuda.conf << EOF &&
/opt/cuda/lib64
/opt/cuda/nvvm/lib64
/opt/cuda/extras/CUPTI/lib64
EOF

ldconfig

Now in order to use the toolkit, it needs to be included in the path.

As the root user, create the profile (dependent on The Bash Shell Startup Files) for CUDA:

cat > /etc/profile.d/cuda.sh << "EOF"
# Begin /etc/profile.d/cuda.sh

pathprepend /opt/cuda/bin           PATH

# End /etc/profile.d/cuda.sh
EOF

Nå henter du hovedprofilen:

source /etc/profile

Contents

For a full package listing, check Arch's CUDA package contents as the full list is too expansive to list here.