You can flatten loops completely with the chess_flatten_loop pragma. Flattening is useful for small loops that
the AI Engine compiler
does not optimally automated.
chess_loop_count pragma. Refer to the following
example:for(int i=0;i<6;i++) chess_flatten_loop {...}
for(...) chess_loop_count(6) chess_flatten_loop {...}
With chess_unroll_loop(N), the loop
body can be duplicated N-1 times, and the loop
count is divided by N. The loop can also be
completely unrolled by chess_unroll_loop(*). The
loop is unrolled and rewritten as a repeated sequence of similar independent
statements.
chess_unroll_loop(N) creates an additional
preamble loop. When the loop count is known at compile time, this preamble loop
fully unrolls. However, if the loop bound is not a compile-time constant but is
guaranteed to be a multiple of N, use chess_unroll_loop_assuming_multiple(N) instead. This
prevents the extra preamble loop, reducing program memory usage.
Loop flattening occurs in the final scheduling phase such that code generation still uses the loop construct. Unlike loop flattening, loop unrolling duplicates iterations of code, and the duplicated codes can be compiled differently. You can use unrolling to improve software pipelining of loops, but it can place a burden on scheduling if the unrolled loop count is large.