[llvm-dev] [RFC] Value Range Based Optimization Opportunity in LLVM

Daniel Berlin via llvm-dev llvm-dev at lists.llvm.org
Thu Aug 31 19:08:11 PDT 2017


NewGVN does some of it.
It will discover if backpropagation through a phi enables an operation to
be put in terms of existing expressions or constants.
It does not track ranges though, only explicit values.

In your ORIG block, if LENGTH can be expressed as a merge of
 already-computed expressions or constants in the program, it will discover
it.

You can stare at examples of this (and compute quite complicated ones if
you wish) at test/Transforms/NewGVN/completeness.ll

Both your examples already have a phi in it in llvm ir, so that is just a
matter of the proper range propagation.
It is really:

int test()
{
 int Ret0 = 0;
  if (!Ptr)
     Ret1= calli(a)
  RetPhi = PHI(Ret0, Ret1)
  return RetPhi;
}

It should already be possible to determine the value of Ret0 to be 0 based
on ranges without duplicating anything, and the extra return doesn't give
you anything.

If you want to do it based on ranges:  a combination of a value range
computation using the existing sparse propagation engine, and a transform
at phi nodes like we use for NewGVN, should be able to handle what you want
here.    The existing lazy value info may not get an optimal answer for
various reasons (it is trying to propagate in the wrong direction, so it
loses some context)

You could also use the same basic infrastructure that predicateinfo uses,
and rename info at points the ranges could have changed to get additional
precision.
 (unlike predicateinfo, which renames when there are branches).

There are quite a number of papers on making SSA forms that are effective
at range propagation. PredicateInfo is building pruned e-ssa, which is the
basis of a number of range analysis (see
http://homepages.dcc.ufmg.br/~fernando/publications/papers/CGO13_raphael.pdf
and the slides at
http://laure.gonnord.org/pro/research/ER03_2015/RangeAnalysis.pdf).

The only case you should ever need to duplicate code is when the expression
is something not already computed in the program.  That's not the case for
your first example, it can be done without code duplication.  For your
second example, it would require insertion, but you could know ahead of
time which computations you actually need to insert.



On Thu, Aug 31, 2017 at 6:22 PM, Hal Finkel via llvm-dev <
llvm-dev at lists.llvm.org> wrote:

>
> On 08/31/2017 03:54 PM, Tony Jiang via llvm-dev wrote:
>
> Hi All,
>
> We have recently found some optimization opportunities created by
> replicating code into branches in order to enable optimization. In general,
> the optimization opportunity we are pursuing is like the following.
>
> Given pseudo-code:
>
> // block A
> if (some condition)
>   // block B
> // block C
>
> If it can be efficiently proven that some portion of block C can be
> simplified had control flow not gone through the if statement, it might be
> useful to convert this CFG into a diamond and hoist that portion of block C
> into both block B and the new block.
>
>
> Consider the following example:
>
>
>
> int test(int *Ptr, int a, int b, int c, int d) {
>   int Ret = 0;
>   if (__builtin_expect(!Ptr, 0)) {
>     Ret = calli(a);
>     // return Ret / (a|1) / (b|1) / (c|1) / (d|1); // Copy return to here
>   }
>   return Ret / (a|1) / (b|1) / (c|1) / (d|1); // This can be simplified to
> return 0
> }
>
> In this case, replicating the return statement in the branch allows the
> optimizer to prove the value of Ret at the end of the function is 0 and
> eliminate the arithmetic calculations.
>
> A second example:
>
> unsigned long funcReturningArbitraryi64(unsigned char *p);
> #define LENGTH(uv)  ( (uv) < 0x80             ? 1 :  \
>                       (uv) < 0x800            ? 2 :  \
>                       (uv) < 0x10000          ? 3 :  \
>                       (uv) < 0x200000         ? 4 :  \
>                       (uv) < 0x4000000        ? 5 :  \
>                       (uv) < 0x80000000       ? 6 : 7 )
>
> int func(unsigned char *p, bool flag)
> {
>   unsigned long c = *p;
>   int len;
>   // ...
> #ifdef _ORIG
>   if(flag) {
>     // ...
>     c = funcReturningArbitraryi64(p);
>   }
> len = LENGTH(c);
> #else
>   if(flag) {
>     // ...
>     c = funcReturningArbitraryi64(p);
>     len = LENGTH(c);
>   } else {
>     len = LENGTH(c);
>   }
> #endif
>
>   // ...
>
>   return len;
> }
>
> In this case, we see that creating an else block and replicating the
> return statement in both the if and else branch (like the code snippet
> guarded by the #else) enables the macro UNISKIP in the else branch to be
> optimized.
>
>
> Most of the examples we have come up with so far are centered around value
> ranges along the conditional branches. When the range of values a symbol
> can have along different branches is provably different, opportunities for
> optimization may arise. However, this likely isn't the only category of
> optimizations that could benefit from this.
>
> Is there an existing transformation in LLVM that should be doing this
> already that is missing this opportunity? If not, we would like to pursue
> adding this. Of course, this optimization would be subject to a cost model
> as it may result in code growth. For example, it may not be advantageous to
> do this if the simplified branch is cold. If anyone has any
> comments/suggestions we are very much interested in hearing them.
>
>
> We have two transformations that track ranges along CFG edges using
> LazyValueInfo: JumpThreading and CorrelatedValuePropagation. I don't think
> that either does what you're proposing.
>
>  -Hal
>
>
>
>
> Regards,
>
>
> Tony Jiang, M.Sc.
> LLVM PPC Backend Development
> IBM Toronto Lab, C2/712/8200/MKM
> 8200 Warden Ave, Markham, L6G 1C7
> Email: *jtony at ca.ibm.com* <nemanjai at ca.ibm.com>
> Phone: 905-413-3676 <(905)%20413-3676>
>
>
> _______________________________________________
> LLVM Developers mailing listllvm-dev at lists.llvm.orghttp://lists.llvm.org/cgi-bin/mailman/listinfo/llvm-dev
>
>
> --
> Hal Finkel
> Lead, Compiler Technology and Programming Languages
> Leadership Computing Facility
> Argonne National Laboratory
>
>
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>
>
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