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README.md

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## Docker
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Docker images are now available for [download](https://hub.docker.com/r/tinkertools/tinker9).
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The executables included in these images were compiled on a recent computer. It is known that they will not run on the machines with very old CPUs. If this is a problem for you, please write a new issue and provide us with more details. Thank you.
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The executables included in these images were compiled on a recent computer. It is known that they will not run on the machines with very old CPUs. If this is a problem for you, please write a new issue and provide us with more details.
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## Installation Steps
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1. [Prerequisites](doc/manual/m/install/preq.rst)
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See [Citations](https://tinkerdoc.readthedocs.io/en/latest/text/cite.html) for details. -->
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## User Manual (In Progress)
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## User Manual (in progress)
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The HTML version is hosted on [readthedocs](https://tinker9-manual.readthedocs.io)
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and the [PDF](https://tinker9-manual.readthedocs.io/_/downloads/en/latest/pdf/)
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version is accessible from the same webpage.

doc/manual/m/install/preq.rst

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A relatively recent NVIDIA GPU is mandatory for the GPU code.
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Nothing special is needed for the CPU code.
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The oldest NVIDIA GPU Tinker9 has been tested on is GeForce GTX 675MX (compute capability 3.0).
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**Operating Systems and Compilers**
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In order to compile the GPU code, the most recent
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In order to compile the GPU code with full functionality, a recent
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`NVIDIA HPC SDK <https://www.developer.nvidia.com/hpc-sdk>`_
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is preferred for the OpenACC directives. Due to its limitations,
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the GPU code is unavailable on macOS.
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the *full* version is unavailable on macOS.
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For Linux, we need:
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- GNU or Intel Fortran compiler.
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- Recent C++ compiler that supports C++11 syntax.
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- CMake 3.15 or newer.
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- (GPU code only) NVIDIA HPC SDK with OpenACC support, and CUDA with nvcc.
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- If NVIDIA driver has been installed correctly, *nvidia-smi* should be
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available.
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We have successfully built Tinker9 on Windows WSL2 Ubuntu with
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For Windows, we have successfully built Tinker9 on Windows WSL2 Ubuntu with
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CUDA 11.0 and NVHPC 20.9. Please proceed to
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`this NVIDIA webpage <https://docs.nvidia.com/cuda/wsl-user-guide/index.html>`_
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for more details.
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The majority of the functionalities are also implemented in CUDA.
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To compile this subset (PureCuda) of the code, NVIDIA HPC SDK is not mandatory.
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Please refer to *Build Tinker9 with CMake* for the flags to compile
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the *PureCuda* GPU kernels.
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It is even possible to compile and run the *PureCuda* version on macOS
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(El Capitan 10.13 or earlier), if suitable drivers and CUDA toolkits are installed.
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If the calculation selects one of the missing functionalities only implemented
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in OpenACC, the program will throw a runtime error.
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**Using NVIDIA HPC SDK on Clusters**
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Prior to rebranding, the current NVIDIA HPC SDK was known as the PGI compiler
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more recent gcc and PGI versions were available via the *module* program,
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the most recent PGI compiler (2019) was still configured with gcc 4.8.5
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by default, which had a very bad support for C++11.
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Since I didn't have root privilege on the cluster, I had to use
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Without root privilege on the cluster, we had to use
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a custom *localrc* file by running the following command to
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reconfigure PGI compiler with gcc 7.4.0:
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- `ClangFormat <https://clang.llvm.org/docs/ClangFormat.html>`_:
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to format the source code.
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- `Doxygen <https://www.doxygen.nl>`_: to generate developer guides.
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- `Sphinx <https://www.sphinx-doc.org>`_: to generate user manual.
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- PDF version also depends on `TeX <https://www.tug.org/begin.html>`_.
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- HTML theme from *pip*.
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- `Doxygen <https://www.doxygen.nl>`_: to generate developer guides.
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.. code-block:: bash
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pip install -U Sphinx
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pip install pydata-sphinx-theme
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python3 -m venv env-tinker9doc
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source env-tinker9doc/bin/activate
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pip3 install -r path_to/doc/manual/requirements.txt

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