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镜像自地址 https://gitee.com/sunhf/gprMax.git 已同步 2025-08-04 11:36:52 +08:00
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Cleaned up instructions on path variables.

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Craig Warren
2019-02-13 09:56:22 +00:00
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docs/source/gpu.rst
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@@ -11,8 +11,9 @@ Extra installation steps for GPU usage
The following steps provide guidance on how to install the extra components to allow gprMax to run on your NVIDIA GPU:
1. Install the `NVIDIA CUDA Toolkit <https://developer.nvidia.com/cuda-toolkit>`_. You can follow the Installation Guides in the `NVIDIA CUDA Toolkit Documentation <http://docs.nvidia.com/cuda/index.html#installation-guides>`_ You must ensure the version of CUDA you install is compatible with the compiler you are using. This information can usually be found in a table in the CUDA Installation Guide under System Requirements. You may need to add the location of the CUDA compiler (:code:`nvcc`) to your user path environment variable, e.g. :code:`C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.0\bin` or :code:`/Developer/NVIDIA/CUDA-10.0/bin`.
2. Install the pycuda Python module. Open a Terminal (Linux/macOS) or Command Prompt (Windows), navigate into the top-level gprMax directory, and if it is not already active, activate the gprMax conda environment :code:`conda activate gprMax`. Run :code:`pip install pycuda`
1. Install the `NVIDIA CUDA Toolkit <https://developer.nvidia.com/cuda-toolkit>`_. You can follow the Installation Guides in the `NVIDIA CUDA Toolkit Documentation <http://docs.nvidia.com/cuda/index.html#installation-guides>`_ You must ensure the version of CUDA you install is compatible with the compiler you are using. This information can usually be found in a table in the CUDA Installation Guide under System Requirements.
2. You may need to add the location of the CUDA compiler (:code:`nvcc`) to your user path environment variable, e.g. for Windows :code:`C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.0\bin` or Linux/macOS :code:`/Developer/NVIDIA/CUDA-10.0/bin`.
3. Install the pycuda Python module. Open a Terminal (Linux/macOS) or Command Prompt (Windows), navigate into the top-level gprMax directory, and if it is not already active, activate the gprMax conda environment :code:`conda activate gprMax`. Run :code:`pip install pycuda`
Running gprMax using GPU(s)
===========================