Renaming CUDA Quantum to CUDA-Q (#1587)

Author: bettinaheim

Building.md

@@ -1,7 +1,7 @@
-# Building CUDA Quantum from Source
+# Building CUDA-Q from Source
 
-To learn more about how to use CUDA Quantum, please take a look at the [CUDA
-Quantum Documentation][cuda_quantum_docs]. The page also contains [installation
+To learn more about how to use CUDA-Q, please take a look at the [CUDA-Q
+Documentation][cuda_quantum_docs]. The page also contains [installation
 instructions][official_install] for released packages and nightly builds.
 
 [cuda_quantum_docs]: https://nvidia.github.io/cuda-quantum/latest
@@ -10,18 +10,18 @@ instructions][official_install] for released packages and nightly builds.
     https://nvidia.github.io/cuda-quantum/latest/data_center_install.html
 
 This document is intended for anyone who wants to develop their own
-modifications of, or contributions to, this code base. If you want to build CUDA
-Quantum from source for the purpose of installing it on a system that is not
+modifications of, or contributions to, this code base. If you want to build
+CUDA-Q from source for the purpose of installing it on a system that is not
 officially supported by our distributed packages, please take a look at our
 [installation guide][data_center_install] instead.
 
-To build the CUDA Quantum source code locally, fork this repository and follow
-the [instructions for setting up your environment](./Dev_Setup.md). Once you
-have done that, you should be able to run the [build
-script](./scripts/build_cudaq.sh) to build and install CUDA Quantum in a local
-folder. The path where CUDA Quantum will be installed can be configured by
-setting the environment variable `CUDAQ_INSTALL_PREFIX`. If you customize this
-path or do not work in our development container, you either need to invoke the
+To build the CUDA-Q source code locally, fork this repository and follow the
+[instructions for setting up your environment](./Dev_Setup.md). Once you have
+done that, you should be able to run the [build
+script](./scripts/build_cudaq.sh) to build and install CUDA-Q in a local folder.
+The path where CUDA-Q will be installed can be configured by setting the
+environment variable `CUDAQ_INSTALL_PREFIX`. If you customize this path or do
+not work in our development container, you either need to invoke the
 built/installed binaries with the full path or modify your path variables as
 follows:
 
@@ -31,18 +31,17 @@ export PYTHONPATH="${CUDAQ_INSTALL_PREFIX}:${PYTHONPATH}"
 ```
 
 Our development container comes with a pre-built version of LLVM which is used
-to build CUDA Quantum. If you are working outside our container, please see the
-instructions for [building CUDA Quantum with a custom LLVM
-version](#building-cuda-quantum-with-a-custom-llvm-version).
+to build CUDA-Q. If you are working outside our container, please see the
+instructions for [building CUDA-Q with a custom LLVM
+version](#building-cuda-q-with-a-custom-llvm-version).
 
-Once you have built CUDA Quantum, you should be able to run the tests and
-confirm that they pass by navigating to the `build` folder and entering the
-command `ctest`. If all tests pass, you are all set to [start
-developing](./Developing.md).
+Once you have built CUDA-Q, you should be able to run the tests and confirm that
+they pass by navigating to the `build` folder and entering the command `ctest`.
+If all tests pass, you are all set to [start developing](./Developing.md).
 
 ## GPU accelerated backends
 
-CUDA Quantum comes with a range of simulator backends for testing and debugging
+CUDA-Q comes with a range of simulator backends for testing and debugging
 application code. In addition to simulators that run on CPUs, there are also
 multiple backends leveraging [cuQuantum][cuquantum] and [cuTensor][cutensor] for
 GPU accelerated simulation. You can take a look at the
@@ -60,11 +59,11 @@ detected running the command `nvidia-smi` in your development environment.
 [cutensor]: https://developer.nvidia.com/cutensor
 [nvidia_driver]: https://www.nvidia.com/download/index.aspx
 
-## Building CUDA Quantum with a custom LLVM version
+## Building CUDA-Q with a custom LLVM version
 
-CUDA Quantum is intended to be built using the LLVM commit that the submodule is
-set to (currently LLVM 16.0.6). If you need to update the LLVM commit, or if you
-are not using the pre-built version of that commit in our development container,
+CUDA-Q is intended to be built using the LLVM commit that the submodule is set
+to (currently LLVM 16.0.6). If you need to update the LLVM commit, or if you are
+not using the pre-built version of that commit in our development container,
 LLVM will need to be built from source. ***Building with LLVM >= 17.x is not
 currently supported*** due to the QIR specification's requirement to use typed
 pointers. LLVM 17.x removed the ability to use typed pointers and instead now
@@ -81,10 +80,9 @@ libraries should be installed:
 export LLVM_INSTALL_PREFIX=<installation_path>
 ```
 
-The CUDA Quantum [build script](./scripts/build_cudaq.sh) checks if
-`llvm-config` is available in the bin subfolder of that directory, and will
-automatically invoke the [LLVM build script](./scripts/build_llvm.sh) if it is
-not.
+The CUDA-Q [build script](./scripts/build_cudaq.sh) checks if `llvm-config` is
+available in the bin subfolder of that directory, and will automatically invoke
+the [LLVM build script](./scripts/build_llvm.sh) if it is not.
 
 Please note that building LLVM may take a while and you should have about 64GB
 of memory available for the build. Please configure your Docker container

CITATION.cff

@@ -1,8 +1,8 @@
 cff-version: 1.2.0
-title: 'CUDA Quantum'
+title: 'CUDA-Q'
 message: 'If you use this software, please cite it as below.'
 authors:
-  - name: "The CUDA Quantum development team"
+  - name: "The CUDA-Q development team"
 license: Apache-2.0
 license-url: "https://github.com/NVIDIA/cuda-quantum/blob/main/LICENSE"
 repository-code: "https://github.com/NVIDIA/cuda-quantum"

Code_of_Conduct.md

@@ -1,7 +1,7 @@
 # Code of Conduct
 
-This document outlines the code of conduct followed and enforced for the CUDA
-Quantum project. This Code of Conduct is adapted from the [Contributor
+This document outlines the code of conduct followed and enforced for the CUDA-Q
+project. This Code of Conduct is adapted from the [Contributor
 Covenant][homepage], version 1.4, available [here][codeofconduct]. For answers
 to common questions about this code of conduct, see the [FAQs][faqs].
 

Contributing.md

@@ -1,7 +1,7 @@
 # Contributing
 
-Thank you for your interest in contributing to CUDA Quantum! Based on the type
-of contribution, it will fall into three categories:
+Thank you for your interest in contributing to CUDA-Q! Based on the type of
+contribution, it will fall into three categories:
 
 1. Report a bug, feature request, or documentation issue:
 
@@ -10,20 +10,20 @@ of contribution, it will fall into three categories:
     them, scheduling them for a release. If you believe the issue needs priority
     attention comment on the issue to notify the team.
 
-1. Share your work built upon CUDA Quantum:
+1. Share your work built upon CUDA-Q:
 
     We would love to hear more about your work! Please share with us on
     [NVIDIA/cudaq GitHub
     Discussions](https://github.com/NVIDIA/cuda-quantum/discussions) or consider
     contributing to our [examples](./docs/sphinx/examples/)! We also take any
-    CUDA Quantum related questions on this forum.
+    CUDA-Q related questions on this forum.
 
 1. Implement a feature or bug-fix:
 
     Please file an [issue][cuda_quantum_issues] on the repository and express
-    your interest in contributing to its implementation. Someone from the CUDA
-    Quantum team will respond on the issue to discuss how to best proceed with
-    the suggestion. For more information regarding contributing to the code
-    base, see also [Developing.md](./Developing.md).
+    your interest in contributing to its implementation. Someone from the CUDA-Q
+    team will respond on the issue to discuss how to best proceed with the
+    suggestion. For more information regarding contributing to the code base,
+    see also [Developing.md](./Developing.md).
 
 [cuda_quantum_issues]: https://github.com/NVIDIA/cuda-quantum/issues

Dev_Setup.md

@@ -48,11 +48,11 @@ others tools to support specialized development workflows. To work with our
 development container please install the [Development Containers
 extension][dev_container_extension].
 
-Create a local clone of your fork of the CUDA Quantum repository, navigate to
-that folder, and open VS Code by executing the command `code .`. You should now
-get a pop up offering to open the folder in the container. Please select this
-option to work in a pre-configured environment that contains all necessary
-dependencies to build CUDA Quantum:
+Create a local clone of your fork of the CUDA-Q repository, navigate to that
+folder, and open VS Code by executing the command `code .`. You should now get a
+pop up offering to open the folder in the container. Please select this option
+to work in a pre-configured environment that contains all necessary dependencies
+to build CUDA-Q:
 
 - On Mac/Linux: Select the option `Open Folder in Container`
 - On Windows: Select the option `Clone Repository in Container Volume` for the
@@ -69,9 +69,9 @@ The container also defines which extensions will be [loaded
 automatically](.devcontainer/devcontainer.json) when launching it. This does not
 impact your VS Code configuration outside the container environment.
 
-You should now be all set to build CUDA Quantum and run tests. Please open a
-terminal in VS Code and follow the instructions [here](./Building.md) to confirm
-that everything works as expected.
+You should now be all set to build CUDA-Q and run tests. Please open a terminal
+in VS Code and follow the instructions [here](./Building.md) to confirm that
+everything works as expected.
 
 [vs_code]: https://code.visualstudio.com/download
 [dev_container_extension]:
@@ -86,12 +86,11 @@ The development container in this repository is configured with extensions to
 facilitate working with MLIR and LLVM files. The [MLIR
 extension][mlir_extension] requires a language server to work properly. The
 `cudaq-lsp-server` tool in this repository extends the [MLIR Language
-Server](https://mlir.llvm.org/docs/Tools/MLIRLSP/) to add support for CUDA
-Quantum specific dialects. It recognizes files with extensions `.mlir` and
-`.qke`.
+Server](https://mlir.llvm.org/docs/Tools/MLIRLSP/) to add support for CUDA-Q
+specific dialects. It recognizes files with extensions `.mlir` and `.qke`.
 
-The `cudaq-lsp-server` is built when running the [CUDA Quantum build
-script](./scripts/build_cudaq.sh) as described in [Building CUDA Quantum from
+The `cudaq-lsp-server` is built when running the [CUDA-Q build
+script](./scripts/build_cudaq.sh) as described in [Building CUDA-Q from
 Source](./Building.md). If you customize the installation location, you will
 need to either add that location to your path, or edit the value of
 `mlir.server_path` in your workspace settings for the extension to work
@@ -104,18 +103,18 @@ properly.
 
 If you have followed the instructions for working inside the provided
 development container (recommended) you are all set and can proceed to [Getting
-Started with Developing CUDA Quantum](./Building.md).
+Started with Developing CUDA-Q](./Building.md).
 
 If you do not leverage the container definition provided in this repository, you
 will need to manually install all prerequisites for building the code on this
 repository, and configure your preferred IDE for working with Python, C++, MLIR,
 and LLVM components. To install all necessary build and runtime dependencies,
 please follow the instructions in our [official guide][data_center_install] for
-building and installing CUDA Quantum from source. The guide details how to get
-a fully featured CUDA Quantum installation that can be deployed on a system other
-than the one used for the build. For development purposes, components/certain
-prerequisites can be omitted as needed, and additional tools and flags for
-debugging purposes may be beneficial.
+building and installing CUDA-Q from source. The guide details how to get a fully
+featured CUDA-Q installation that can be deployed on a system other than the one
+used for the build. For development purposes, components/certain prerequisites
+can be omitted as needed, and additional tools and flags for debugging purposes
+may be beneficial.
 
 [data_center_install]:
     https://nvidia.github.io/cuda-quantum/latest/data_center_install.html

Developing.md

@@ -1,11 +1,11 @@
-# Getting Started with Developing CUDA Quantum
+# Getting Started with Developing CUDA-Q
 
 This document contains guidelines for contributing to the code in this
 repository. This document is relevant primarily for contributions to the `nvq++`
-compiler, the CUDA Quantum runtime, or to the integrated simulation backends. If
-you would like to contribute applications and examples that use the CUDA Quantum
-platform, please follow the instructions for [installing CUDA
-Quantum][official_install] instead.
+compiler, the CUDA-Q runtime, or to the integrated simulation backends. If you
+would like to contribute applications and examples that use the CUDA-Q platform,
+please follow the instructions for [installing CUDA-Q][official_install]
+instead.
 
 [official_install]: https://nvidia.github.io/cuda-quantum/latest/install.html
 
@@ -14,7 +14,7 @@ Quantum][official_install] instead.
 Before getting started with development, please create a fork of this repository
 if you haven't done so already and make sure to check out the latest version on
 the `main` branch. After following the instruction for [setting up your
-development environment](./Dev_Setup.md) and [building CUDA Quantum from
+development environment](./Dev_Setup.md) and [building CUDA-Q from
 source](Building.md), you should be able to confirm that you can run the tests
 and examples using your local build. If you edit [this
 file](./runtime/nvqir/CircuitSimulator.h) to add a print statement
@@ -33,7 +33,7 @@ nvq++ "$CUDAQ_REPO_ROOT/docs/sphinx/examples/cpp/algorithms/grover.cpp" -o grove
 ```
 
 When working on compiler internals, it can be useful to look at intermediate
-representations for CUDA Quantum kernels.
+representations for CUDA-Q kernels.
 
 To see how the kernels in [this
 example](./docs/sphinx/examples/cpp/algorithms/grover.cpp) are translated, you
@@ -54,28 +54,27 @@ quake-translate --convert-to=qir
 
 ## Code style
 
-With regards to code format and style, we distinguish public APIs and CUDA
-Quantum internals. Public APIs should follow the style guide of the respective
-language, specifically [this guide][cpp_style] for C++, and the [this
-guide][python_style] for Python. The CUDA Quantum internals on the other hand
-follow the [MLIR/LLVM style guide][llvm_style]. Please ensure that your code
-includes comprehensive doc comments as well as a comment at the top of the file
-to indicating its purpose.
+With regards to code format and style, we distinguish public APIs and CUDA-Q
+internals. Public APIs should follow the style guide of the respective language,
+specifically [this guide][cpp_style] for C++, and the [this guide][python_style]
+for Python. The CUDA-Q internals on the other hand follow the [MLIR/LLVM style
+guide][llvm_style]. Please ensure that your code includes comprehensive doc
+comments as well as a comment at the top of the file to indicating its purpose.
 
 [python_style]: https://google.github.io/styleguide/pyguide.html
 [cpp_style]: https://www.gnu.org/prep/standards/standards.html
 [llvm_style]: https://llvm.org/docs/CodingStandards.html
 
 ## Testing and debugging
 
-CUDA Quantum tests are categorized as unit tests on runtime library code and
+CUDA-Q tests are categorized as unit tests on runtime library code and
 `FileCheck` tests on compiler code output. All code added under the runtime
 libraries should have an accompanying test added to the appropriate spot in the
 `unittests` folder. All code that directly impacts compiler code should have an
 accompanying `FileCheck` test. These tests are located in the `test` folder.
 
-When running a CUDA Quantum executable locally, the verbosity of the output can
-be configured by setting the `CUDAQ_LOG_LEVEL` environment variable. Setting its
+When running a CUDA-Q executable locally, the verbosity of the output can be
+configured by setting the `CUDAQ_LOG_LEVEL` environment variable. Setting its
 value to `info` will enable printing of informational messages, and setting its
 value to `trace` generates additional messages to trace the execution. These
 logs can be directed to a file by setting the `CUDAQ_LOG_FILE` variable when