[llvm-dev] RFC: DenseMap grow() slowness

[Hal Finkel via llvm-dev]

----- Original Message -----

> From: escha at apple.com
> To: "Hal Finkel" <hfinkel at anl.gov>
> Cc: "llvm-dev" <llvm-dev at lists.llvm.org>
> Sent: Tuesday, March 15, 2016 5:17:46 PM
> Subject: Re: [llvm-dev] RFC: DenseMap grow() slowness

> > On Mar 15, 2016, at 3:15 PM, Hal Finkel < hfinkel at anl.gov > wrote:
> 

> > ----- Original Message -----
> 

> > > From: "via llvm-dev" < llvm-dev at lists.llvm.org >
> > 
> 
> > > To: "llvm-dev" < llvm-dev at lists.llvm.org >
> > 
> 
> > > Sent: Tuesday, March 15, 2016 5:07:29 PM
> > 
> 
> > > Subject: [llvm-dev] RFC: DenseMap grow() slowness
> > 
> 

> > > There’s a few passes in LLVM that make heavy use of a big
> > > DenseMap,
> > > one that potentially gets filled with up to 1 entry for each
> > > instruction in the function. EarlyCSE is the best example, but
> > > Reassociate and MachineCSE have this to some degree as well
> > > (there
> > > might be others?). To put it simply: at least in my profile,
> > > EarlyCSE spends ~1/5 of its time growing DenseMaps. This is kind
> > > of…
> > > bad.
> > 
> 

> > > grow() is inherently slow because it needs to rehash and reinsert
> > > everything. This means growing a DenseMap costs much, much more
> > > than
> > > growing, for example, a vector. I talked about this with a few
> > > people and here are some possibilities we’ve come up with to
> > > improve
> > > this (some of which probably aren’t what we want):
> > 
> 

> > > 1. Use a map that doesn’t require rehashing and reinsertion to
> > > grow.
> > > Chaining lets you do this, but std::unordered_map is probably so
> > > much slower than DenseMap we’d lose more than we gain.
> > 
> 
> > > 2. Include the hash code in the map so that we don’t have to
> > > rehash.
> > > 32 bits more per entry (or whatever), and it might not help that
> > > much, since we still have to do the whole reinsertion routine.
> > 
> 
> > > 3. Pre-calculate an estimate as to the map size we need. For
> > > example,
> > > in EarlyCSE, this is possibly gross overestimate of size needed:
> > 
> 

> > > unsigned InstCount = 0 ;
> > 
> 
> > > unsigned LoadCount = 0 ;
> > 
> 
> > > unsigned CallCount = 0 ;
> > 
> 
> > > for ( inst_iterator FI = inst_begin ( F ), FE = inst_end ( F );
> > > FI
> > > !=
> > > FE; ++FI) {
> > 
> 
> > > if (FI-> mayReadOrWriteMemory ())
> > 
> 
> > > ++LoadCount;
> > 
> 
> > > else if ( isa < CallInst >(*FI))
> > 
> 
> > > ++CallCount;
> > 
> 
> > > else
> > 
> 
> > > ++InstCount;
> > 
> 
> > > }
> > 
> 
> > > AvailableValues . resize (InstCount);
> > 
> 
> > > AvailableLoads . resize (LoadCount);
> > 
> 
> > > AvailableCalls . resize (CallCount);
> > 
> 

> > > But it does the job, and saves ~20% of time in EarlyCSE on my
> > > profiles. Yes, iterating over the entire function is way cheaper
> > > than grow(). Downsides are that while it’s still bounded by
> > > function
> > > size, it could end up allocating a good bit more depending on —
> > > in
> > > EarlyCSE’s case — the control flow/dominator structure.
> > 
> 
> > This last option makes perfect sense to me. One thing we might be
> > able to do regarding the extra memory overhead is, instead of
> > actually resizing up front, to start with a relatively small map,
> > but use the function size to set the growth factor so that we grow
> > only a small number of times (say once) in the worst case.
> 
> Growing fewer times doesn’t actually help much from what I can tell,
> because the largest grow() always dominates the cost of the others.

> For example, if you start with 8 buckets, and you end up needing 512
> buckets, and you grow 2x at a time:

> 8, 16, 32, 64, 128, 256, 512

> The final grow() costs as much as all the others combined. So if you
> grow 4x at a time:

> 8, 32, 128, 512

> you don’t actually save much; I think the gain is probably bounded at
> a factor of 2.
Understood; but that wasn't what I had in mind exactly. What about if we added a threshold and a target size (set as above), so that the growth factors would do this: 

8, 16, 32, 64, 128, ..., threshold (I suppose this will be big), target size 

i.e. once you hit some threshold, we assume the map will be large, and we jump right to your precalculated target size? Would that bring the benefits while mitigating much of the extra memory overhead? 

-Hal 

> —escha

-- 

Hal Finkel 
Assistant Computational Scientist 
Leadership Computing Facility 
Argonne National Laboratory 
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