Unroll macro

Might as well take a look at Base.@nexpr, Unrolled.jl and KernalAbstractions.jl.

This package provides the unroll and tuplegen macros. The unroll macro in Julia unrolls simple for-loops. For example, the following code:

@unroll for i = 1 : 2
   x += a[i]
end

will macro-expand as:

x += a[1]
x += a[2]

For this to be possible, the loop bounds must be known at the time of macro-expansion. A common case is that they are literal constant values as in the above example.
The loop bounds may include symbolic constants that are global within the module:

const LOOPBOUND = 2
function myfunct()
   @unroll for i = 1 : LOOPBOUND
      <etc>
   end
end

The unroll macro can be nested.

Finally, the unroll macro will search for conditionals that depend on the loop counter and unroll these as well. For example, the call:

@unroll for i = 1 : 4
   if mod(i,2) == 1
      a += b[i]
   else
      a += 2*b[i]
   end
end

will macro-expand to:

a += b[1]
a += 2*b[2]
a += b[3]
a += 2*b[4]

The tuplegen macro

The tuplegen macro generates fixed-length tuples using comprehension-like syntax. For example:

v = @tuplegen [(i==2)? i * 6 : i for i = 1 : 4]

macro-expands to:

v = (1, 2*6, 3, 4)

and therefore generates the tuple (1,12,3,4).
Without the @tuplegen call, this same statement would generate the array [1,12,3,4]. It is possible to generate tuples from comprehensions via the following standard statement:

v = tuple([(i==2)? i * 6 : i for i = 1 : 4]...)

but this statement is less efficient because it creates a heap-allocated array as a temporary.

Here is a more complicated example of @tuplegen. Suppose 2-by-2 matrices are represented as 2-tuples of 2-tuples, e.g., ((1,2),(5,7)) stands for:

  1  2
  5  7

Then 2-by-2 matrix multiplication may be defined by:

mtxmult(a,b) = @tuplegen [@tuplegen [a[i][1]*b[1][j] + a[i][2]*b[2][j] 
                                       for j = 1 : 2]
                           for i = 1 : 2]

This definition generates unrolls into four expressions on the right-hand side and works as expected:

julia> mtxmult(((1,2),(5,7)),((4,1),(2,8)))
((8,17),(34,61))

As with the @unroll macro, the loop bounds for @tuplegen must be known at macro-expansion time. In particular, the following plausible attempt to define a generic function for addition of arbitrary fixed-length tuples (so that (1,7)+(-2,3) yields (-1,10)) does not work::

+{N}(a::NTuple{N}, b::NTuple{N}) = @tuplegen [a[i]+b[i] for i=1:N]

because the type parameter N is not known at the time of macro expansion; instead it is determined later by the dispatch mechanism. If someone knows how to fix this, please create an issue or pull request. (It is possible to write generic addition for tuples via the more complicated generated-function mechanism.)

Cautionary notes

• The loop index must be a simple variable (e.g., the loop cannot be of the form for (k,v) in mydict or something similar).
• The loop index is matched symbolically by the macro. This means that the same symbol may not be used in the loop body with a different meaning (e.g., qualified by a different module name).
• If the loop index is somehow concealed inside the loop body, say with an eval/parse statement, then the macro will fail.
• The macro calls eval to obtain the loop bounds and also to check whether if conditions are satisfied. This means that the loop should not include statements with side effects (like print) in either the loop bounds or in conditionals, since these statements may get unexpectedly executed during the macro expansion phase.