{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# The Devito domain specific language: an overview\n",
"\n",
"This notebook presents an overview of the Devito symbolic language, used to express and discretise operators, in particular partial differential equations (PDEs).\n",
"\n",
"For convenience, we import all Devito modules:"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"from devito import *"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## From equations to code in a few lines of Python\n",
"\n",
"The main objective of this tutorial is to demonstrate how Devito and its [SymPy](http://www.sympy.org/en/index.html)-powered symbolic API can be used to solve partial differential equations using the finite difference method with highly optimized stencils in a few lines of Python. We demonstrate how computational stencils can be derived directly from the equation in an automated fashion and how Devito can be used to generate and execute, at runtime, the desired numerical scheme in the form of optimized C code.\n",
"\n",
"\n",
"## Defining the physical domain\n",
"\n",
"Before we can begin creating finite-difference (FD) stencils we will need to give Devito a few details regarding the computational domain within which we wish to solve our problem. For this purpose we create a `Grid` object that stores the physical `extent` (the size) of our domain and knows how many points we want to use in each dimension to discretise our data.\n",
"\n",
""
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Grid[extent=(1.0, 1.0), shape=(5, 6), dimensions=(x, y)]"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"grid = Grid(shape=(5, 6), extent=(1., 1.))\n",
"grid"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Functions and data\n",
"\n",
"To express our equation in symbolic form and discretise it using finite differences, Devito provides a set of `Function` types. A `Function` object:\n",
"\n",
"1. Behaves like a `sympy.Function` symbol\n",
"2. Manages data associated with the symbol\n",
"\n",
"To get more information on how to create and use a `Function` object, or any type provided by Devito, we can take a look at the documentation."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
" Tensor symbol representing a discrete function in symbolic equations.\n",
"\n",
" A Function carries multi-dimensional data and provides operations to create\n",
" finite-differences approximations.\n",
"\n",
" A Function encapsulates space-varying data; for data that also varies in time,\n",
" use TimeFunction instead.\n",
"\n",
" Parameters\n",
" ----------\n",
" name : str\n",
" Name of the symbol.\n",
" grid : Grid, optional\n",
" Carries shape, dimensions, and dtype of the Function. When grid is not\n",
" provided, shape and dimensions must be given. For MPI execution, a\n",
" Grid is compulsory.\n",
" space_order : int or 3-tuple of ints, optional\n",
" Discretisation order for space derivatives. Defaults to 1. ``space_order`` also\n",
" impacts the number of points available around a generic point of interest. By\n",
" default, ``space_order`` points are available on both sides of a generic point of\n",
" interest, including those nearby the grid boundary. Sometimes, fewer points\n",
" suffice; in other scenarios, more points are necessary. In such cases, instead of\n",
" an integer, one can pass a 3-tuple ``(o, lp, rp)`` indicating the discretization\n",
" order (``o``) as well as the number of points on the left (``lp``) and right\n",
" (``rp``) sides of a generic point of interest.\n",
" shape : tuple of ints, optional\n",
" Shape of the domain region in grid points. Only necessary if ``grid`` isn't given.\n",
" dimensions : tuple of Dimension, optional\n",
" Dimensions associated with the object. Only necessary if ``grid`` isn't given.\n",
" dtype : data-type, optional\n",
" Any object that can be interpreted as a numpy data type. Defaults\n",
" to ``np.float32``.\n",
" staggered : Dimension or tuple of Dimension or Stagger, optional\n",
" Define how the Function is staggered.\n",
" initializer : callable or any object exposing the buffer interface, optional\n",
" Data initializer. If a callable is provided, data is allocated lazily.\n",
" allocator : MemoryAllocator, optional\n",
" Controller for memory allocation. To be used, for example, when one wants\n",
" to take advantage of the memory hierarchy in a NUMA architecture. Refer to\n",
" `default_allocator.__doc__` for more information.\n",
" padding : int or tuple of ints, optional\n",
" .. deprecated:: shouldn't be used; padding is now automatically inserted.\n",
"\n",
" Allocate extra grid points to maximize data access alignment. When a tuple\n",
" of ints, one int per Dimension should be provided.\n",
"\n",
" Examples\n",
" --------\n",
" Creation\n",
"\n",
" >>> from devito import Grid, Function\n",
" >>> grid = Grid(shape=(4, 4))\n",
" >>> f = Function(name='f', grid=grid)\n",
" >>> f\n",
" f(x, y)\n",
" >>> g = Function(name='g', grid=grid, space_order=2)\n",
" >>> g\n",
" g(x, y)\n",
"\n",
" First-order derivatives through centered finite-difference approximations\n",
"\n",
" >>> f.dx\n",
" Derivative(f(x, y), x)\n",
" >>> f.dy\n",
" Derivative(f(x, y), y)\n",
" >>> g.dx\n",
" Derivative(g(x, y), x)\n",
" >>> (f + g).dx\n",
" Derivative(f(x, y) + g(x, y), x)\n",
"\n",
" First-order derivatives through left/right finite-difference approximations\n",
"\n",
" >>> f.dxl\n",
" Derivative(f(x, y), x)\n",
"\n",
" Note that the fact that it's a left-derivative isn't captured in the representation.\n",
" However, upon derivative expansion, this becomes clear\n",
"\n",
" >>> f.dxl.evaluate\n",
" f(x, y)/h_x - f(x - h_x, y)/h_x\n",
" >>> f.dxr\n",
" Derivative(f(x, y), x)\n",
"\n",
" Second-order derivative through centered finite-difference approximation\n",
"\n",
" >>> g.dx2\n",
" Derivative(g(x, y), (x, 2))\n",
"\n",
" Notes\n",
" -----\n",
" The parameters must always be given as keyword arguments, since SymPy\n",
" uses ``*args`` to (re-)create the dimension arguments of the symbolic object.\n",
" \n"
]
}
],
"source": [
"print(Function.__doc__)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Ok, let's create a function $f(x, y)$ and look at the data Devito has associated with it. Please note that it is important to use explicit keywords, such as `name` or `grid` when creating `Function` objects."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/latex": [
"$\\displaystyle f{\\left(x,y \\right)}$"
],
"text/plain": [
"f(x, y)"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"f = Function(name='f', grid=grid)\n",
"f"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Data([[0., 0., 0., 0., 0., 0.],\n",
" [0., 0., 0., 0., 0., 0.],\n",
" [0., 0., 0., 0., 0., 0.],\n",
" [0., 0., 0., 0., 0., 0.],\n",
" [0., 0., 0., 0., 0., 0.]], dtype=float32)"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"f.data"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"By default, Devito `Function` objects use the spatial dimensions `(x, y)` for 2D grids and `(x, y, z)` for 3D grids. To solve a PDE over several timesteps a time dimension is also required by our symbolic function. For this Devito provides an additional function type, the `TimeFunction`, which incorporates the correct dimension along with some other intricacies needed to create a time stepping scheme."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/latex": [
"$\\displaystyle g{\\left(t,x,y \\right)}$"
],
"text/plain": [
"g(t, x, y)"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"g = TimeFunction(name='g', grid=grid)\n",
"g"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Since the default time order of a `TimeFunction` is `1`, the shape of `f` is `(2, 5, 6)`, i.e. Devito has allocated two buffers to represent `g(t, x, y)` and `g(t + dt, x, y)`:"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(2, 5, 6)"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"g.shape"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Derivatives of symbolic functions\n",
"\n",
"The functions we have created so far all act as `sympy.Function` objects, which means that we can form symbolic derivative expressions from them. Devito provides a set of shorthand expressions (implemented as Python properties) that allow us to generate finite differences in symbolic form. For example, the property `f.dx` denotes $\\frac{\\partial}{\\partial x} f(x, y)$ - only that Devito has already discretised it with a finite difference expression. There are also a set of shorthand expressions for left (backward) and right (forward) derivatives:\n",
"\n",
"| Derivative | Shorthand | Discretised | Stencil |\n",
"| ---------- |:---------:|:-----------:|:-------:|\n",
"| $\\frac{\\partial}{\\partial x}f(x, y)$ (right) | `f.dxr` | $\\frac{f(x+h_x,y)}{h_x} - \\frac{f(x,y)}{h_x}$ | |\n",
"| $\\frac{\\partial}{\\partial x}f(x, y)$ (left) | `f.dxl` | $\\frac{f(x,y)}{h_x} - \\frac{f(x-h_x,y)}{h_x}$ | |\n",
"\n",
"A similar set of expressions exist for each spatial dimension defined on our grid, for example `f.dy` and `f.dyl`. Obviously, one can also take derivatives in time of `TimeFunction` objects. For example, to take the first derivative in time of `g` you can simply write:"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/latex": [
"$\\displaystyle \\frac{\\partial}{\\partial t} g{\\left(t,x,y \\right)}$"
],
"text/plain": [
"Derivative(g(t, x, y), t)"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"g.dt"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We may also want to take a look at the stencil Devito will generate based on the chosen discretisation:"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/latex": [
"$\\displaystyle - \\frac{g{\\left(t,x,y \\right)}}{dt} + \\frac{g{\\left(t + dt,x,y \\right)}}{dt}$"
],
"text/plain": [
"-g(t, x, y)/dt + g(t + dt, x, y)/dt"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"g.dt.evaluate"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"There also exist convenient shortcuts to express the forward and backward stencil points, `g(t+dt, x, y)` and `g(t-dt, x, y)`."
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/latex": [
"$\\displaystyle g{\\left(t + dt,x,y \\right)}$"
],
"text/plain": [
"g(t + dt, x, y)"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"g.forward"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/latex": [
"$\\displaystyle g{\\left(t - dt,x,y \\right)}$"
],
"text/plain": [
"g(t - dt, x, y)"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"g.backward"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"And of course, there's nothing to stop us taking derivatives on these objects:"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/latex": [
"$\\displaystyle \\frac{\\partial}{\\partial t} g{\\left(t + dt,x,y \\right)}$"
],
"text/plain": [
"Derivative(g(t + dt, x, y), t)"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"g.forward.dt"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/latex": [
"$\\displaystyle \\frac{\\partial}{\\partial y} g{\\left(t + dt,x,y \\right)}$"
],
"text/plain": [
"Derivative(g(t + dt, x, y), y)"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"g.forward.dy"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## A linear convection operator\n",
"\n",
"**Note:** The following example is derived from [step 5](http://nbviewer.ipython.org/github/barbagroup/CFDPython/blob/master/lessons/07_Step_5.ipynb) in the excellent tutorial series [CFD Python: 12 steps to Navier-Stokes](http://lorenabarba.com/blog/cfd-python-12-steps-to-navier-stokes/).\n",
"\n",
"In this simple example we will show how to derive a very simple convection operator from a high-level description of the governing equation. We will go through the process of deriving a discretised finite difference formulation of the state update for the field variable $u$, before creating a callable `Operator` object. Luckily, the automation provided by SymPy makes the derivation very nice and easy.\n",
"\n",
"The governing equation we want to implement is the linear convection equation:\n",
"$$\\frac{\\partial u}{\\partial t}+c\\frac{\\partial u}{\\partial x} + c\\frac{\\partial u}{\\partial y} = 0.$$\n",
"\n",
"Before we begin, we must define some parameters including the grid, the number of timesteps and the timestep size. We will also initialize our velocity `u` with a smooth field:"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"tags": [
"nbval-ignore-output"
]
},
"outputs": [
{
"data": {
"image/png": 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\n",
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