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> **Note:** Starting with cuQuantum Python v25.06, cuQuantum C libraries including cuDensityMat, cuStateVec and cuTensorNet are no longer build-time dependencies. However, they are still required at runtime.
@@ -29,37 +29,36 @@ To compile and install cuQuantum Python from source, please follow the steps bel
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1. Clone the [NVIDIA/cuQuantum](https://github.com/NVIDIA/cuQuantum) repository: `git clone https://github.com/NVIDIA/cuQuantum`
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2. Set `CUDA_PATH` to point to your CUDA installation
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3.[optional] Set `CUQUANTUM_ROOT` to point to your cuQuantum installation
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4.[optional] Set `CUTENSOR_ROOT` to point to your cuTENSOR installation
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5.[optional] Make sure cuQuantum and cuTENSOR are visible in your `LD_LIBRARY_PATH`
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6. Switch to the directory containing the Python implementation: `cd cuQuantum/python`
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7. Build and install:
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- Run `pip install .` if you skip Step 3-5 above
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3.[optional] Make sure cuQuantum and cuTENSOR are visible in your `LD_LIBRARY_PATH`
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4. Switch to the directory containing the Python implementation: `cd cuQuantum/python`
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5. Build and install:
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- Run `pip install .` if you skip Step 3 above
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- Run `pip install -v --no-deps --no-build-isolation .` otherwise (advanced)
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Notes:
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- For Step 7, if you are building from source for testing/developing purposes you'd likely want to insert a `-e` flag before the last period (so `pip ... .` becomes `pip ... -e .`):
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- For Step 5, if you are building from source for testing/developing purposes you'd likely want to insert a `-e` flag before the last period (so `pip ... .` becomes `pip ... -e .`):
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*`-e`: use the "editable" (in-place) mode
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*`-v`: enable more verbose output
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*`--no-deps`: avoid installing the *run-time* dependencies
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*`--no-build-isolation`: reuse the current Python environment instead of creating a new one for building the package (this avoids installing any *build-time* dependencies)
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- As an alternative to setting `CUQUANTUM_ROOT`, `CUSTATEVEC_ROOT`, `CUTENSORNET_ROOT` and `CUDENSITYMAT_ROOT` can be set to point to the cuStateVec, cuTensorNet and cuDensityMat libraries, respectively. The latter three environment variables take precedence if defined.
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- Please ensure that you use consistent binaries and packages for either CUDA 11 or 12. Mixing-and-matching will result in undefined behavior.
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- Please ensure that you use consistent binaries and packages for either CUDA 12 or 13. Mixing-and-matching will result in undefined behavior.
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## Running
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### Requirements
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Runtime dependencies of the cuQuantum Python package include:
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* An NVIDIA GPU with compute capability 7.0+
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* Driver: Linux (450.80.02+ for CUDA 11, 525.60.13+ for CUDA 12)
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* CUDA Toolkit 11.x or 12.x
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* cuStateVec 1.9.0+
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* cuTensorNet 2.8.0+
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* cuDensityMat >=0.2.0, <0.3.0
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* An NVIDIA GPU with compute capability 7.5+
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* Driver: Linux (525.60.13+ for CUDA 12, 580.65.06+ for CUDA 13)
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* CUDA Toolkit 12.x or 13.x
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* cuStateVec 1.10.0+
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* cuTensorNet 2.9.0+
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* cuDensityMat >=0.3.0, <0.4.0
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* Python >=3.11, <3.14
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* NumPy v1.21+
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* nvmath-python ==0.6.0
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* cuda-bindings >=12.9.2, <13.0.0 for CUDA 12 or cuda-bindings >=13.0.1, <14.0.0
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* CuPy v13.0.0+ (see [installation guide](https://docs.cupy.dev/en/stable/install.html))
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* PyTorch v1.10+ (optional, see [installation guide](https://pytorch.org/get-started/locally/))
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* Qiskit v1.4.2+ (optional, see [installation guide](https://qiskit.org/documentation/getting_started.html))
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Known issues:
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- If a system has multiple copies of cuTENSOR, one of which is installed in a default system path, the Python runtime could pick it up despite cuQuantum Python is linked to another copy installed elsewhere, potentially causing a version-mismatch error. The proper fix is to remove cuTENSOR from the system paths to ensure the visibility of the proper copy. **DO NOT ATTEMPT** to use `LD_PRELOAD` to overwrite it --- it could cause hard to debug behaviors!
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- Please ensure that you use consistent binaries and packages for either CUDA 11 or 12. Mixing-and-matching will result in undefined behavior.
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- Please ensure that you use consistent binaries and packages for either CUDA 12 or 13. Mixing-and-matching will result in undefined behavior.
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