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已同步 2025-08-06 20:46:52 +08:00
Updates for version 3.1.0 - Big Smoke. These updates are predominately to enable gprMax to be run on GPUs using NVIDIA CUDA.
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27
docs/source/gpu.rst
普通文件
27
docs/source/gpu.rst
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.. _gpu:
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**********
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Using GPUs
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**********
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The most computationally intensive parts of gprMax, which are the FDTD solver loops, can optionally be executed using General-purpose computing on graphics processing units (GPGPU). This has been achieved through use of the NVIDIA CUDA programming environment, therefore a `NVIDIA CUDA-Enabled GPU <https://developer.nvidia.com/cuda-gpus>`_ is required to take advantage of the GPU-based solver.
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Extra installation steps for GPU usage
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======================================
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The following steps provide guidance on how to install the extra components to allow gprMax to run on your GPU:
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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>`_
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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:`source activate gprMax` (Linux/macOS) or :code:`activate gprMax` (Windows). Run :code:`conda install pycuda`
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Run a test model
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================
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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:`source activate gprMax` (Linux/macOS) or :code:`activate gprMax` (Windows)
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Run one of the test models:
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.. code-block:: none
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(gprMax)$ python -m gprMax user_models/cylinder_Ascan_2D.in -gpu
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python_scripting
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openmp_mpi
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gpu
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.. toctree::
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:maxdepth: 2
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.. _openmp-mpi:
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******************
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Parallel execution
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******************
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*********************
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OpenMP, MPI, and HPCs
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*********************
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OpenMP
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======
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