***************
Getting Started
***************

In this section, we briefly descibe how to install *cuQuantum* which contains both *cuStateVec* and *cuTensorNet*. 

For C/C++ users, the easiest way to get started is through the installation from conda-forge described below.
More detailed explanations on installation, compilation and usage of each component can be found in :doc:`cuStateVec Guide <custatevec/getting_started>` and :doc:`cuTensorNet Guide <cutensornet/getting_started>`.

For Python users, *cuQuantum Python* delivers all functionalities of *cuStateVec* and *cuTensorNet* with Python APIs. 
The easist way to get started with *cuQuantum Python* is also through installation from conda-forge described below. For more detailed guide on the installation and usage, 
please refer to :doc:`cuQuantum Python Guide <python/README>`.

==================================
Install cuQuantum from conda-forge
==================================

If you already have a Conda environment set up (if not, Miniforge/Mambaforge is a great `starting point <https://github.com/conda-forge/miniforge>`_),
*cuQuantum* can be easily installed from the conda-forge channel, via:

.. code-block:: bash

   conda install -c conda-forge cuquantum

The ``conda`` solver will install all required dependencies for you. The package is installed to the current ``$CONDA_PREFIX``, so you can simply update the environment variable as follows:

.. code-block:: bash

   export CUQUANTUM_ROOT=$CONDA_PREFIX

.. note::

   To enable automatic MPI parallelism for *cuTensorNet*, you can install ``cuquantum`` with an MPI from conda-forge, e.g., ``conda install -c conda-forge cuquantum openmpi``. 
   For detailed guide, please refer to :doc:`cuTensorNet Guide <cutensornet/getting_started>`.

=========================================
Install cuQuantum Python from conda-forge
=========================================

Similar to the *cuQuantum* installation introduced above, *cuQuantum Python* can also be easily installed from the conda-forge channel, via:

.. code-block:: bash

   conda install -c conda-forge cuquantum-python

The ``conda`` solver will install all required dependencies for you. 

=====================================
Install cuQuantum from NVIDIA DevZone
=====================================

*cuQuantum* package can be downloaded from https://developer.nvidia.com/cuQuantum-downloads?target_os=Linux.
Further, the *cuTensorNet* component relies upon the functionality of the cuTENSOR package, available for download at https://developer.nvidia.com/cutensor.

We will be using the tarball distribution to illustrate the process. Once the tarball file is downloaded to ``CUQUANTUM_ROOT`` directory, 
you can unpack it via:

.. code-block:: bash

   tar zxvf cuquantum-linux-xxxxx-aa.bb.cc.dd-archive.tar.xz

and update the environment variable:

.. code-block:: bash

   export CUQUANTUM_ROOT=/path/to/where/tarball/is/unpacked

.. note::

   To enable automatic MPI parallelism for *cuTensorNet*, please refer to :doc:`cuTensorNet Guide <cutensornet/getting_started>`.


======================
cuQuantum Dependencies
======================

Below we provide a summary of dependencies required for all *cuQuantum* components:

----------
cuStateVec
----------

.. list-table:: 
   :widths: 50 50

   * - GPU Architectures
     - Volta, Turing, Ampere, Ada, Hopper
   * - NVIDIA GPU with Compute Capability
     - 7.0+
   * - CUDA
     - 11.x
   * - CPU architectures
     - x86_64, ppc64le, ARM64
   * - Operating System
     - Linux
   * - Driver
     - 450.80.02+ (Linux)

-----------
cuTensorNet
-----------

.. list-table::
   :widths: 50 50

   * - GPU Architectures
     - Volta, Turing, Ampere, Ada, Hopper
   * - NVIDIA GPU with Compute Capability
     - 7.0+
   * - CUDA
     - 11.x
   * - CPU architectures
     - x86_64, ppc64le, ARM64
   * - Operating System
     - Linux
   * - Driver
     - 450.80.02+ (Linux)
   * - cuTENSOR
     - 1.6.1+

----------------
cuQuantum Python
----------------

.. list-table::
   :widths: 50 25 25
   :header-rows: 1

   * - 
     - When Building
     - When Running
   * - Python
     - 3.8+
     - 3.8+
   * - pip
     - 22.3.1+
     - N/A
   * - setuptools
     - >=61.0.0
     - N/A
   * - wheel
     - >=0.34.0
     - N/A
   * - Cython
     - >=0.29.22,<3
     - N/A
   * - cuStateVec
     - 1.2.0
     - ~=1.1
   * - cuTensorNet
     - 2.0.0
     - ~=2.0
   * - NumPy
     - N/A
     - v1.19+
   * - CuPy (see `CuPy installation guide <https://docs.cupy.dev/en/stable/install.html>`_)
     - N/A
     - v9.5.0+
   * - PyTorch (optional, see `PyTorch installation guide <https://pytorch.org/get-started/locally/>`_)
     - N/A
     - v1.10+
   * - Qiskit (optional, see `Qiskit installation guide <https://qiskit.org/documentation/getting_started.html>`_)
     - N/A
     - v0.24.0+
   * - Cirq (optional, see `Cirq installation guide <https://quantumai.google/cirq/install>`_)
     - N/A
     - v0.6.0+
   * - mpi4py (optional, see `mpi4py installation guide <https://mpi4py.readthedocs.io/en/stable/install.html>`_)
     - N/A
     - v3.1.0+

-------------------
cuQuantum Appliance
-------------------

.. list-table:: 
   :widths: 50 50

   * - CUDA
     - 11.x
   * - Driver
     - 470.42.01+ (Linux)