suboptimal ghc code generation in IO vs equivalent pure code case

Sat May 14 20:05:29 UTC 2016

Well, a few weeks ago Bertram Felgenhauer came up with a version of IO that
acts more like lazy ST. That could be just the thing. He placed it in the
public domain/CC0 and told me I could put it up on Hackage if I want. I'll
try to do that this week, but no promises. I could forward his email if you
just want to try it out.
On May 14, 2016 2:31 PM, "Harendra Kumar" <harendra.kumar at gmail.com> wrote:

> The difference seems to be entirely due to memory pressure. At list size
> 1000 both pure version and IO version perform equally. But as the size of
> the list increases the pure version scales linearly while the IO version
> degrades exponentially. Here are the execution times per list element in ns
> as the list size increases:
>
> Size of list  Pure       IO
> 1000           8.7          8.3
> 10000         8.7          18
> 100000       8.8          63
> 1000000     9.3          786
>
> This seems to be due to increased GC activity in the IO case. The GC stats
> for list size 1 million are:
>
> IO case:       %GC     time      66.1%  (61.1% elapsed)
> Pure case:   %GC     time       2.6%  (3.3% elapsed)
>
> Not sure if there is a way to write this code in IO monad which can reduce
> this overhead.
>
> -harendra
>
>
> On 14 May 2016 at 17:10, Harendra Kumar <harendra.kumar at gmail.com> wrote:
> >
> > You are right about the way IO code is generated because of the ordering
> semantics. The IO version builds the list entirely in a recursive fashion
> before returning it while the pure code builds it lazily. I wrote very
> simple versions to keep things simpler:
> >
> > Pure version:
> >
> > f [] = []
> > f (x : xs) = x : f xs
> >
> >
> > time                11.08 ms   (10.86 ms .. 11.34 ms)
> > Measured for a million elements in the list
> >
> >      104,041,264 bytes allocated in the heap
> >           16,728 bytes copied during GC
> >           35,992 bytes maximum residency (1 sample(s))
> >           21,352 bytes maximum slop
> >                1 MB total memory in use (0 MB lost due to fragmentation)
> >
> >
> > IO version:
> > f [] = return []
> > f (x : xs) = do
> >     rest <- f xs
> >     return $ x : rest
> >
> > time                 79.66 ms   (75.49 ms .. 82.55 ms)
> >
> >      208,654,560 bytes allocated in the heap
> >      121,045,336 bytes copied during GC
> >       27,679,344 bytes maximum residency (8 sample(s))
> >          383,376 bytes maximum slop
> >               66 MB total memory in use (0 MB lost due to fragmentation)
> >
> > Even though this is a small program not doing much and therefore
> enhancing even small differences to a great degree, I am not sure if I can
> completely explain the difference in slowness of the order of 7.5x by just
> the recursive vs lazy building of the list. I am wondering if there is
> anything that is worth further investigating and improving here.
> >
> > -harendra
> >
> > On 12 May 2016 at 05:41, Dan Doel <dan.doel at gmail.com> wrote:
> > >
> > > On Tue, May 10, 2016 at 4:45 AM, Harendra Kumar
> > > <harendra.kumar at gmail.com> wrote:
> > > > Thanks Dan, that helped. I did notice and suspect the update frame
> and the
> > > > unboxed tuple but given my limited knowledge about ghc/core/stg/cmm
> I was
> > > > not sure what is going on. In fact I thought that the intermediate
> tuple
> > > > should get optimized out since it is required only because of the
> realworld
> > > > token which is not real. But it might be difficult to see that at
> this
> > > > level?
> > >
> > > The token exists as far as the STG level is concerned, I think,
> > > because that is the only thing ensuring that things happen in the
> > > right order. And the closure must be built to have properly formed
> > > STG. So optimizing away the closure building would have to happen at a
> > > level lower than STG, and I guess there is no such optimization. I'm
> > > not sure how easy it would be to do.
> > >
> > > > What you are saying may be true for the current implementation but
> in theory
> > > > can we eliminate the intermediate closure?
> > >
> > > I don't know. I'm a bit skeptical that building this one closure is
> > > the only thing causing your code to be a factor of 5 slower. For
> > > instance, another difference in the core is that the recursive call
> > > corresponding to the result s2 happens before allocating the
> > > additional closure. That is the case statement that unpacks the
> > > unboxed tuple. And the whole loop happens this way, so it is actually
> > > building a structure corresponding to the entire output list in memory
> > > rather eagerly.
> > >
> > > By contrast, your pure function is able to act in a streaming fashion,
> > > if consumed properly, where only enough of the result is built to keep
> > > driving the rest of the program. It probably runs in constant space,
> > > while your IO-based loop has a footprint linear in the size of the
> > > input list (in addition to having slightly more overhead per character
> > > because of the one extra thunk), because it is a more eager program.
> > >
> > > And having an asymptotically larger memory footprint is more likely to
> > > explain a 5x slowdown than allocating one extra thunk for each list
> > > concatenation, I think. (Of course, it could also be some other
> > > factor, as well.)
> > >
> > > You should probably run with +RTS -s (compiling with -rtsopts), and
> > > see if the IO version has a much larger maximum residency.
> > >
> > > Anyhow, this is fundamental to writing the algorithm using IO. It's an
> > > algorithm that's a sequence of steps that happen in order, the number
> > > of steps is proportional to the input list, and part of those steps is
> > > putting stuff in memory for the results.
> > >
> > > > So why is that? Why can't we generate (++) inline similar to (:)?
> How do we
> > > > make this decision? Is there a theoretical reason for this or this
> is just
> > > > an implementation artifact?
> > >
> > > The difference between these two is that (++) is a function call, and
> > > (:) is a constructor. Constructors are a special case, and don't need
> > > to have all the provisions that functions in general do. The best way
> > > to learn what the differences are is probably to read the paper about
> > > the STG machine.
> > >
> > > Hope this is a more fruitful lead, but it may be that there's not a
> > > lot that can be done, without doing some baroque things to your
> > > algorithm, because of the necessity of its using IO.
> > >
> > > -- Dan
>
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