In this tutorial we will learn how to build, compose, and transform Iteration/Expression Trees (IETs).

Part II - Bottom Up

Dimensions are the building blocks of both Iterations and Expressions.



In [1]:

    
from devito import SpaceDimension, TimeDimension

dims = {'i': SpaceDimension(name='i'),
        'j': SpaceDimension(name='j'),
        'k': SpaceDimension(name='k'),
        't0': TimeDimension(name='t0'),
        't1': TimeDimension(name='t1')}

dims









    Out[1]:





{'i': i, 'j': j, 'k': k, 't0': t0, 't1': t1}

Elements such as Scalars, Constants and Functions are used to build SymPy equations.



In [2]:

    
from devito import Grid, Constant, Function, TimeFunction
from devito.types import Array, Scalar

grid = Grid(shape=(10, 10))
symbs = {'a': Scalar(name='a'),
         'b': Constant(name='b'),
         'c': Array(name='c', shape=(3,), dimensions=(dims['i'],)).indexify(),
         'd': Array(name='d', 
                    shape=(3,3), 
                    dimensions=(dims['j'],dims['k'])).indexify(),
         'e': Function(name='e', 
                       shape=(3,3,3), 
                       dimensions=(dims['t0'],dims['t1'],dims['i'])).indexify(),
         'f': TimeFunction(name='f', grid=grid).indexify()}
symbs









    Out[2]:





{'a': a, 'b': b, 'c': c[i], 'd': d[j, k], 'e': e[t0, t1, i], 'f': f[t, x, y]}

An IET Expression wraps a SymPy equation. Below, DummyEq is a subclass of sympy.Eq with some metadata attached. What, when and how metadata are attached is here irrelevant.



In [3]:

    
from devito.ir.iet import Expression
from devito.ir.equations import DummyEq
from devito.tools import pprint

def get_exprs(a, b, c, d, e, f):
    return [Expression(DummyEq(a, b + c + 5.)),
            Expression(DummyEq(d, e - f)),
            Expression(DummyEq(a, 4 * (b * a))),
            Expression(DummyEq(a, (6. / b) + (8. * a)))]

exprs = get_exprs(symbs['a'],
                  symbs['b'],
                  symbs['c'],
                  symbs['d'],
                  symbs['e'],
                  symbs['f'])

pprint(exprs)









    



<Expression a = b + c[i] + 5.0>
<Expression d[j, k] = e[t0, t1, i] - f[t, x, y]>
<Expression a = 4*a*b>
<Expression a = 8.0*a + 6.0/b>

An Iteration typically wraps one or more Expressions.



In [4]:

    
from devito.ir.iet import Iteration

def get_iters(dims):
    return [lambda ex: Iteration(ex, dims['i'], (0, 3, 1)),
            lambda ex: Iteration(ex, dims['j'], (0, 5, 1)),
            lambda ex: Iteration(ex, dims['k'], (0, 7, 1)),
            lambda ex: Iteration(ex, dims['t0'], (0, 4, 1)),
            lambda ex: Iteration(ex, dims['t1'], (0, 4, 1))]

iters = get_iters(dims)

Here, we can see how blocks of Iterations over Expressions can be used to build loop nests.



In [5]:

    
def get_block1(exprs, iters):
    # Perfect loop nest:
    # for i
    #   for j
    #     for k
    #       expr0
    return iters[0](iters[1](iters[2](exprs[0])))
    
def get_block2(exprs, iters):
    # Non-perfect simple loop nest:
    # for i
    #   expr0
    #   for j
    #     for k
    #       expr1
    return iters[0]([exprs[0], iters[1](iters[2](exprs[1]))])

def get_block3(exprs, iters):
    # Non-perfect non-trivial loop nest:
    # for i
    #   for s
    #     expr0
    #   for j
    #     for k
    #       expr1
    #       expr2
    #   for p
    #     expr3
    return iters[0]([iters[3](exprs[0]),
                     iters[1](iters[2]([exprs[1], exprs[2]])),
                     iters[4](exprs[3])])

block1 = get_block1(exprs, iters)
block2 = get_block2(exprs, iters)
block3 = get_block3(exprs, iters)

pprint(block1), print('\n')
pprint(block2), print('\n')
pprint(block3)









    



<Iteration i::i::(0, 3, 1)>
  <Iteration j::j::(0, 5, 1)>
    <Iteration k::k::(0, 7, 1)>
      <Expression a = b + c[i] + 5.0>


<Iteration i::i::(0, 3, 1)>
  <Expression a = b + c[i] + 5.0>
  <Iteration j::j::(0, 5, 1)>
    <Iteration k::k::(0, 7, 1)>
      <Expression d[j, k] = e[t0, t1, i] - f[t, x, y]>


<Iteration i::i::(0, 3, 1)>
  <Iteration t0::t0::(0, 4, 1)>
    <Expression a = b + c[i] + 5.0>
  <Iteration j::j::(0, 5, 1)>
    <Iteration k::k::(0, 7, 1)>
      <Expression d[j, k] = e[t0, t1, i] - f[t, x, y]>
      <Expression a = 4*a*b>
  <Iteration t1::t1::(0, 4, 1)>
    <Expression a = 8.0*a + 6.0/b>

And, finally, we can build Callable kernels that will be used to generate C code. Note that Operator is a subclass of Callable.



In [6]:

    
from devito.ir.iet import Callable

kernels = [Callable('foo', block1, 'void', ()),
           Callable('foo', block2, 'void', ()),
           Callable('foo', block3, 'void', ())]

print('kernel no.1:\n' + str(kernels[0].ccode) + '\n')
print('kernel no.2:\n' + str(kernels[1].ccode) + '\n')
print('kernel no.3:\n' + str(kernels[2].ccode) + '\n')









    



kernel no.1:
void foo()
{
  for (int i = 0; i <= 3; i += 1)
  {
    for (int j = 0; j <= 5; j += 1)
    {
      for (int k = 0; k <= 7; k += 1)
      {
        a = b + c[i] + 5.0F;
      }
    }
  }
}

kernel no.2:
void foo()
{
  for (int i = 0; i <= 3; i += 1)
  {
    a = b + c[i] + 5.0F;
    for (int j = 0; j <= 5; j += 1)
    {
      for (int k = 0; k <= 7; k += 1)
      {
        d[j][k] = e[t0][t1][i] - f[t][x][y];
      }
    }
  }
}

kernel no.3:
void foo()
{
  for (int i = 0; i <= 3; i += 1)
  {
    for (int t0 = 0; t0 <= 4; t0 += 1)
    {
      a = b + c[i] + 5.0F;
    }
    for (int j = 0; j <= 5; j += 1)
    {
      for (int k = 0; k <= 7; k += 1)
      {
        d[j][k] = e[t0][t1][i] - f[t][x][y];
        a = 4*a*b;
      }
    }
    for (int t1 = 0; t1 <= 4; t1 += 1)
    {
      a = 8.0F*a + 6.0F/b;
    }
  }
}

An IET is immutable. It can be "transformed" by replacing or dropping some of its inner nodes, but what this actually means is that a new IET is created. IETs are transformed by Transformer visitors. A Transformer takes in input a dictionary encoding replacement rules.



In [7]:

    
from devito.ir.iet import Transformer

# Replaces a Function's body with another
transformer = Transformer({block1: block2})
kernel_alt = transformer.visit(kernels[0])
print(kernel_alt)









    



void foo()
{
  for (int i = 0; i <= 3; i += 1)
  {
    a = b + c[i] + 5.0F;
    for (int j = 0; j <= 5; j += 1)
    {
      for (int k = 0; k <= 7; k += 1)
      {
        d[j][k] = e[t0][t1][i] - f[t][x][y];
      }
    }
  }
}

Specific Expressions within the loop nest can also be substituted.



In [8]:

    
# Replaces an expression with another
transformer = Transformer({exprs[0]: exprs[1]})
newblock = transformer.visit(block1)
newcode = str(newblock.ccode)
print(newcode)









    



for (int i = 0; i <= 3; i += 1)
{
  for (int j = 0; j <= 5; j += 1)
  {
    for (int k = 0; k <= 7; k += 1)
    {
      d[j][k] = e[t0][t1][i] - f[t][x][y];
    }
  }
}



In [9]:

    
from devito.ir.iet import Block
import cgen as c

# Creates a replacer for replacing an expression
line1 = '// Replaced expression'
replacer = Block(c.Line(line1))
transformer = Transformer({exprs[1]: replacer})
newblock = transformer.visit(block2)
newcode = str(newblock.ccode)
print(newcode)









    



for (int i = 0; i <= 3; i += 1)
{
  a = b + c[i] + 5.0F;
  for (int j = 0; j <= 5; j += 1)
  {
    for (int k = 0; k <= 7; k += 1)
    {
      // Replaced expression
      {
      }
    }
  }
}



In [10]:

    
# Wraps an expression in comments
line1 = '// This is the opening comment'
line2 = '// This is the closing comment'
wrapper = lambda n: Block(c.Line(line1), n, c.Line(line2))
transformer = Transformer({exprs[0]: wrapper(exprs[0])})
newblock = transformer.visit(block1)
newcode = str(newblock.ccode)
print(newcode)









    



for (int i = 0; i <= 3; i += 1)
{
  for (int j = 0; j <= 5; j += 1)
  {
    for (int k = 0; k <= 7; k += 1)
    {
      // This is the opening comment
      {
        a = b + c[i] + 5.0F;
      }
      // This is the closing comment
    }
  }
}