Hi Damian —
Taking your three versions:
Original:
forall r in rows do
{
const ref ur = u[r, ..];
for j in cslice do
{
t[r, j] = vmDot(common, ur, vslab[j, ..]);
}
}
} }
Forall expr:
forall r in rows do
{
const ref ur = u[r, ..];
const x = [j in cslice] vmDot(common, ur, vslab[j, ..]);
t[r, cslice] = x;
}
Succinct:
forall r in rows do
{
const x = [j in cslice] vmDot(common, u[r, ..], vslab[j, ..]);
t[r, cslice] = x;
}
slows down seriously, about 25+%.
I believe the difference between the final two is a simple case of Chapel
not doing loop hoisting optimizations for non-trivial expressions.
Specifically, you and I can see that `u[r, ..]` is independent of the
value of 'j' so could be evaluated once and re-used for all iterations of
the 'j' loop, but the Chapel compiler isn't mature enough to do this yet.
So your "Forall expr" version gets an improvement by manually hoisting the
evaluation of that expression out of the loop.
The delta between the original and forall expression version is less
obvious, but I would guess that it could be due to the use of nested
parallelism (though we'd hope that the impact would be more minimal than
5%, at least for loops with large trip counts). Specifically, by default,
'[j in cslice]' will be executed in parallel, but it'll first check to see
whether there's already a task per core, and if so, will serialize the
loop. Maybe this execution-time check is adding the 5% overhead? A way
to check would be to write the initialization of 'x' as:
const x = for j in cslice do vmDot(common, ur, vslab[j, ..]);
If this returned the lost 5%, I think that's the answer.
-Brad
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