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‎.clang-format

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BasedOnStyle: LLVM
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AlwaysBreakTemplateDeclarations: Yes
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IncludeCategories:
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- Regex: '^<'
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Priority: 4
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- Regex: '^"(llvm|llvm-c|clang|clang-c|mlir|mlir-c)/'
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Priority: 3
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- Regex: '^"(qoda|\.\.)/'
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Priority: 2
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- Regex: '.*'
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Priority: 1

‎.gitattributes

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*.sh text eol=lf

‎.gitignore

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# Editor backup files
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*~
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# Patch files
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*.orig
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*.rej
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# Compiled Object files
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*.slo
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*.lo
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*.o
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*.obj
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*.x
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# Precompiled Headers
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*.gch
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*.pch
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# Compiled Dynamic libraries
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*.so
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*.dylib
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*.dll
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# Fortran module files
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*.mod
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*.smod
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# Compiled Static libraries
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*.lai
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*.la
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*.a
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*.lib
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**/Output/
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**/.lit*.txt
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# Executables
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*.exe
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*.out
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*.app
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**/out/
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/*build/
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/*Build/
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/plugins/
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/other_library_builds/
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/.cproject
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/.project
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/.settings/
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**/*.jar
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**/.ptp*
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*.ab
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/dist/
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/*egg*/
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/python/*egg*
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/*tmp*/
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/wheelhouse/
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**/.ipynb_checkpoints
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compile_commands.json
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**/*.dat
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**/.antlr
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__pycache__/
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# IDE files
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.vscode/*
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.theia/*
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# Container files
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**/.docker/*
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# LSP files
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.cache/*
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# LLVM/MLIR files
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*.ll
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*.bc
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# Build results
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[Bb]in/
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[Oo]bj/
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*.bson
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*.csv
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*.bin
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docs/sphinx/_doxygen
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docs/sphinx/_mdgen
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**/_build/*
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# macOS
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.DS_Store

‎.gitmodules

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[submodule "tpls/fmt"]
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path = tpls/fmt
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url = https://github.com/fmtlib/fmt
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[submodule "tpls/googletest-src"]
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path = tpls/googletest-src
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url = https://github.com/google/googletest
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[submodule "tpls/rpclib"]
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path = tpls/rpclib
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url = https://github.com/rpclib/rpclib
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[submodule "tpls/llvm"]
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path = tpls/llvm
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url = https://github.com/llvm/llvm-project.git
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shallow = true
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[submodule "tpls/eigen"]
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path = tpls/eigen
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url = https://gitlab.com/libeigen/eigen.git
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[submodule "tpls/armadillo"]
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path = tpls/armadillo
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url = https://gitlab.com/conradsnicta/armadillo-code.git
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[submodule "tpls/ensmallen"]
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path = tpls/ensmallen
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url = https://github.com/mlpack/ensmallen
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[submodule "tpls/spdlog"]
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path = tpls/spdlog
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url = https://github.com/gabime/spdlog

‎.licenserc.yaml

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header:
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license:
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spdx-id: Apache-2.0
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copyright-owner: NVIDIA Corporation & Affiliates
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software-name: CUDA Quantum
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content: |
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Copyright (c) 2023 NVIDIA Corporation & Affiliates.
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All rights reserved.
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This source code and the accompanying materials are made available under
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the terms of the Apache License 2.0 which accompanies this distribution.
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pattern: |
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Apache License 2.0
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paths:
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- '**'
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paths-ignore:
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- '**/*.md'
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- '**/*.rst'
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- '**/*.patch'
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- '**/*.config'
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- '**/.*'
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- '**/.*/**'
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- '**/Doxyfile.in'
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- 'docs/sphinx/examples'
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- 'LICENSE'
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- 'NOTICE'
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- 'build'
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- 'tpls'
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- 'docs/sphinx/_templates'
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- 'runtime/cudaq/algorithms/optimizers/nlopt/nlopt-src'
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comment: on-failure
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license-location-threshold: 80

‎Building.md

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# Building CUDA Quantum from Source
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To learn more about how to use CUDA Quantum, please take a look at the [CUDA
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Quantum Documentation][cudaq_docs]. The page also contains [installation
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instructions][official_install] for officially released packages.
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[cudaq_docs]: https://developer.nvidia.com/cudaq
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[official_install]: todo
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This document contains instructions for how to build CUDA Quantum from source.
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This is only needed if you would like to try out the latest (unreleased) version
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that is currently under development in this repository and/or if you would like
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to add your own modifications to this code base.
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To build the CUDA Quantum source code locally, fork this repository and follow
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the [instructions for setting up your environment](./Dev_Setup.md). Once you
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have done that, you should be able to run the [build
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script](./scripts/build_cudaq.sh) to build and install CUDA Quantum in a local
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folder. The path where CUDA Quantum will be installed can be configured by
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setting the environment variable `CUDAQ_INSTALL_PREFIX`. If you customize this
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path or do not work in our dev container, you either need to invoke the
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built/installed binaries with the full path or modify your path variables as
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follows:
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```bash
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export PATH="${CUDAQ_INSTALL_PREFIX}/bin:${PATH}"
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export PYTHONPATH="${CUDAQ_INSTALL_PREFIX}:${PYTHONPATH}"
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```
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Our dev container comes with a prebuilt version of LLVM which is used to build
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CUDA Quantum. If you are working outside our container, please see the
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instructions for [building CUDA Quantum with a custom LLVM
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version](#building-cudaq-with-a-custom-llvm-version).
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Once you have built CUDA Quantum, you should be able to run the tests and
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confirm that they pass by navigating to the `build` folder and entering the
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command `ctest`. If all tests pass, you are all set to [start
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developing](./Developing.md).
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## GPU accelerated backends
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CUDA Quantum comes with a range of simulator backends for testing and debugging
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application code. In addition to simulators that run on CPUs, there are also
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multiple backends leveraging [cuQuantum][cuquantum] for GPU accelerated
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simulation. This repository does not require you to have a GPU; if no GPU is
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detected, the corresponding backends will simply be omitted from the build.
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To use or develop GPU-based simulators, you will need to make sure you have a
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suitable NVIDIA GPU with the [latest driver][nvidia_driver] installed. You can
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confirm the GPU is properly detected running the command `nvidia-smi`.
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If you are working in our dev container, please add a `--gpus=all` flag to the
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list of `runArgs` in the
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[.devcontainer/devcontainer.json](.devcontainer/devcontainer.json) file and
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relaunch the container. It is unfortunately not possible to define a dev
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container that enables GPU support depending on the system configuration (see
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[this issue](https://github.com/airo-ugent/airo-ros/issues/17)).
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If you are not working in our dev container, you may need to specify the correct
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path to your cuQuantum installation by setting the environment variable
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`CUQUANTUM_INSTALL_PREFIX`.
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[cuquantum]: https://developer.nvidia.com/cuquantum-sdk
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[nvidia_driver]: https://www.nvidia.com/download/index.aspx
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## Building CUDA Quantum with a custom LLVM version
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CUDA Quantum is intended to be built using the LLVM commit that the submodule is
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set to. If you need to update the LLVM commit, or if you are not using the
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prebuilt version of that commit in our dev container, LLVM will need to be built
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from source. To configure our build scripts, please set the LLVM submodule to
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the desired commit, and set the following environment variable, replacing
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`<installation_path>` with the path where the freshly built LLVM tools and
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libraries should be installed:
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```bash
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export LLVM_INSTALL_PREFIX=<installation_path>
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```
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The CUDA Quantum [build script](./scripts/build_cudaq.sh) checks if
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`llvm-config` is available in the bin subfolder of that directory, and will
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automatically invoke the [LLVM build script](./scripts/build_llvm.sh) if it is
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not.
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Please note that building LLVM may take a while and you should have about 64GB
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of memory available for the build. Please configure your Docker container
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settings accordingly. If you are working on Windows, the amount of resources
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that are available within a container is determined by the WSL settings. Please
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create or modify the [WSL configuration file][wsl_config] if necessary.
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[wsl_config]: https://learn.microsoft.com/en-us/windows/wsl/wsl-config

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