xref: /libCEED/examples/python/tutorial-0-ceed.ipynb (revision 13964f0727a62e5421e6d3b433e838b96a9ce891)

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   "source": [
    "# libCEED for Python examples\n",
    "\n",
    "This is a tutorial to illustrate the main feautures of the Python interface for [libCEED](https://github.com/CEED/libCEED/), the low-level API library for efficient high-order discretization methods developed by the co-design [Center for Efficient Exascale Discretizations](https://ceed.exascaleproject.org/) (CEED) of the [Exascale Computing Project](https://www.exascaleproject.org/) (ECP).\n",
    "\n",
    "While libCEED's focus is on high-order finite/spectral element method implementations, the approach is mostly algebraic and thus applicable to other discretizations in factored form, as explained in the [user manual](https://libceed.org/)."
   ]
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   "source": [
    "## Setting up libCEED for Python"
   ]
  },
  {
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   "metadata": {},
   "source": [
    "Install libCEED for Python by running"
   ]
  },
  {
   "cell_type": "code",
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   "source": [
    "! python -m pip install libceed"
   ]
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   "source": [
    "## Ceed\n",
    "\n",
    "Here we show some basic examples to illustrate the `Ceed` class. In libCEED, Ceeds represent library context representing control of logical hardware resources.\n",
    "\n",
    "Here we illustrate the simple declaration of a `Ceed`, with default resource (which is `/cpu/self`)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import libceed\n",
    "\n",
    "ceed = libceed.Ceed()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can visualize the memory address of the object instantiated by typing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(ceed)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To use a particular backend, for instance `/cpu/self/opt/blocked` you can specify"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ceed = libceed.Ceed('/cpu/self/opt/blocked')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Similarly, if libCEED is built with GPU support, you can specify a GPU backend, e.g., `/gpu/occa` or `/gpu/cuda/gen`."
   ]
  }
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