Thank you for the detailed explanation. I tried it out:
function pretty_fast(features::Vector{Feature})
retval = 0.0
for i in 1 : length(features)
if isa(features[i], A)
x = evaluate(features[i]::A)
elseif isa(features[i], B)
x = evaluate(features[i]::B)
else
x = evaluate(features[i])
end
retval += x
end
retval
end
On my laptop, fast runs in 10 microseconds, pretty_fast in 30, and slow in
210.
On Saturday, April 2, 2016 at 12:24:18 PM UTC-4, Yichao Yu wrote:
>
> On Sat, Apr 2, 2016 at 12:16 PM, Tim Wheeler <timwheel...@gmail.com
> <javascript:>> wrote:
> > Thank you for the comments. In my original code it means the difference
> > between a 30 min execution with memory allocation in the Gigabytes and a
> few
> > seconds of execution with only 800 bytes using the second version.
> > I thought under-the-hood Julia basically runs those if statements anyway
> for
> > its dispatch, and don't know why it needs to allocate any memory.
> > Having the if-statement workaround will be fine though.
>
> Well, if you have a lot of these cheap functions being dynamically
> dispatched I think it is not a good way to use the type. Depending on
> your problem, you may be better off using a enum/flags/dict to
> represent the type/get the values.
>
> The reason for the allocation is that the return type is unknown. It
> should be obvious to see if you check your code with code_warntype.
>
> >
> > On Saturday, April 2, 2016 at 7:26:11 AM UTC-7, Cedric St-Jean wrote:
> >>
> >>
> >>> Therefore there's no way the compiler can rewrite the slow version to
> the
> >>> fast version.
> >>
> >>
> >> It knows that the element type is a Feature, so it could produce:
> >>
> >> if isa(features[i], A)
> >> retval += evaluate(features[i]::A)
> >> elseif isa(features[i], B)
> >> retval += evaluate(features[i]::B)
> >> else
> >> retval += evaluate(features[i])
> >> end
> >>
> >> and it would make sense for abstract types that have few subtypes. I
> >> didn't realize that dispatch was an order of magnitude slower than type
> >> checking. It's easy enough to write a macro generating this expansion,
> too.
> >>
> >> On Saturday, April 2, 2016 at 2:05:20 AM UTC-4, Yichao Yu wrote:
> >>>
> >>> On Fri, Apr 1, 2016 at 9:56 PM, Tim Wheeler <timwheel...@gmail.com>
> >>> wrote:
> >>> > Hello Julia Users.
> >>> >
> >>> > I ran into a weird slowdown issue and reproduced a minimal working
> >>> > example.
> >>> > Maybe someone can help shed some light.
> >>> >
> >>> > abstract Feature
> >>> >
> >>> > type A <: Feature end
> >>> > evaluate(f::A) = 1.0
> >>> >
> >>> > type B <: Feature end
> >>> > evaluate(f::B) = 0.0
> >>> >
> >>> > function slow(features::Vector{Feature})
> >>> > retval = 0.0
> >>> > for i in 1 : length(features)
> >>> > retval += evaluate(features[i])
> >>> > end
> >>> > retval
> >>> > end
> >>> >
> >>> > function fast(features::Vector{Feature})
> >>> > retval = 0.0
> >>> > for i in 1 : length(features)
> >>> > if isa(features[i], A)
> >>> > retval += evaluate(features[i]::A)
> >>> > else
> >>> > retval += evaluate(features[i]::B)
> >>> > end
> >>> > end
> >>> > retval
> >>> > end
> >>> >
> >>> > using ProfileView
> >>> >
> >>> > features = Feature[]
> >>> > for i in 1 : 10000
> >>> > push!(features, A())
> >>> > end
> >>> >
> >>> > slow(features)
> >>> > @time slow(features)
> >>> > fast(features)
> >>> > @time fast(features)
> >>> >
> >>> > The output is:
> >>> >
> >>> > 0.000136 seconds (10.15 k allocations: 166.417 KB)
> >>> > 0.000012 seconds (5 allocations: 176 bytes)
> >>> >
> >>> >
> >>> > This is a HUGE difference! Am I missing something big? Is there a
> good
> >>> > way
> >>> > to inspect code to figure out where I am going wrong?
> >>>
> >>> This is because of type instability as you will find in the
> performance
> >>> tips.
> >>> Note that slow and fast are not equivalent since the fast version only
> >>> accept `A` or `B` but the slow version accepts any subtype of feature
> >>> that you may ever define. Therefore there's no way the compiler can
> >>> rewrite the slow version to the fast version.
> >>> There are optimizations that can be applied to bring down the gap but
> >>> there'll always be a large difference between the two.
> >>>
> >>> >
> >>> >
> >>> > Thank you in advance for any guidance.
> >>> >
> >>> >
> >>> > -Tim
> >>> >
> >>> >
> >>> >
> >>> >
> >>> >
>
