[llvm-dev] Generalizing load/store promotion in LICM

[Philip Reames via llvm-dev]

I'm thinking about making some semi radical changes to load store 
promotion works in LICM, and figured it would be a good idea to get buy 
in before I actually started writing code.  :)

TLDR: legality of sinking stores to exits is hard, can we separate load 
handling into a super aggressive form of PRE, and use predicated stores 
to avoid solving legality question?


Background

We've been seeing an interesting class of problems recently that looks 
roughly like this:

for (int = 0; i < N; i++)
   if (a[i] == 0) // some data dependent check
     g_count++; // conditional load and store to shared location

The critical detail in this example is that g_count is a global location 
which may be accessed concurrently* by multiple threads. The challenge 
here is that we don't know whether the store ever executes, and we're 
not allowed to insert a store along any path that didn't originally 
contain them.  Said differently, if all elements in "a" are non-zero, 
we're not allowed to store to g_count.  We do know that the g_count 
location is dereferenceable though.

(*Please, let's avoid the memory model derailment here.  I'm simplifying 
and C++ language rules aren't real useful for my Java language frontend 
anyways.  In practice, all the access are atomic, but unordered, but 
we'll leave that out of discussion otherwise.)

I have two approaches I'm considering here.  These are orthogonal, but I 
suspect we'll want to implement both.


Proposal A - Use predicated stores in loop exits

The basic idea is that we don't worry about solving the legality 
question above, and just insert a store which is predicated on a 
condition which is true exactly when the original store ran.  In pseudo 
code, this looks something like:

bool StoreLegal = false;
int LocalCount = g_count;
for (int = 0; i < N; i++)
   if (a[i] == 0) {
     LocalCount++;
     StoreLegal = true;
   }
if (StoreLegal) g_count = LocalCount;

There are two obvious concerns here:

 1. The predicated store might be expensive in practice - true for most
    current architectures.
 2. We''re introducing an extra boolean phi cycle around the loop.

Talking to a couple of folks offline at the socials over the last few 
months, the former seems to be the main objection.  I think we can 
control this by restricting this transform to when the loop is believed 
to have a high trip count and the conditional path is taken with some 
frequency.   Getting feedback on this particular point is one of my main 
reasons for writing this mail.

The second objection can frequently be resolved by finding other 
expressions which evaluate to the same boolean.  (In this case, if 
LocalCount != LocalCountOrig assuming i doesn't overflow.)  We already 
have a framework with SCEV to do these replacements. Though, from some 
quick testing, it would definitely need strengthening.  However, SCEV 
can't remove the extra phi in all cases, so we have to be okay with the 
extra phi cycle in the general case.  This seems worthwhile to me, but 
thoughts?


Proposal B - Separate load and store handling into distinct transforms

(For folks I've discussed this with before, this part is all new.)

Thinking about the problem, it finally occurred to me that we can 
decompose the original example into two steps: getting the loads out of 
the loop, and sinking the stores out of the loop.  If we can accomplish 
the former, but not the later, we've still made meaningful progress.

So, what'd we'd essentially have is a load only transformation which 
produces this:
int LocalCount = g_count;
for (int = 0; i < N; i++)
   if (a[i] == 0) {
     LocalCount++;
     g_count = LocalCount;
   }

At this point, we've reduced memory traffic by half, and opened up the 
possibility that other parts of the optimizer can exploit the simplified 
form.  The last point is particular interesting since we generally try 
to canonicalize loads out of loops, and much of the optimizer is tuned 
for a form with as much as possible being loop invariant.  As one 
example, completely by accident, there's some work going on in the 
LoopVectorizer right now to handle such stores to loop invariant 
addresses during vectorization.  Putting the two pieces together would 
let us fully vectorize this loop without needing to sink the stores at all.

In practice, the existing implementation in LICM would cleanly split 
along these lines with little problem.

One way of looking at this load specific transform is as an extreme form 
of PRE (partial redundancy elimination).  Our current PRE implementation 
doesn't handle cases this complicated.

Thoughts?

Philip

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