Aha! tested the same sequence in a non-REPL run and the 1st and 2nd
runtimes after a `precompile` are the same.
On Wednesday, November 25, 2015 at 10:23:04 PM UTC+2, Dan wrote:
>
> I've managed to reproduce the timing peculiarities you described, with a
> different function. In fact, I get the same first run slower behavior even
> with regular functions with -no- keywords. It is almost as if `precompile`
> is not doing the entire job.
> Have you tried, just testing the basic precompile-1st run-2nd run timing
> of a no keyword generic function?
>
> On Tuesday, November 24, 2015 at 9:43:41 PM UTC+2, Tim Holy wrote:
>>
>> I've been experimenting further with SnoopCompile and Immerse/Gadfly,
>> trying to
>> shave off more of the time-to-first-plot. If I pull out all the stops
>> (using the
>> "userimg.jl" strategy), I can get it down to about 2.5 seconds. However,
>> doing
>> the same plot a second time is about 0.02s. This indicates that despite
>> my
>> efforts, there's still a lot that's not being cached.
>>
>> About 0.3s of that total (not much, but it's all I have data on) can be
>> observed via snooping as re-compilation of functions that you might
>> imagine
>> should have been precompiled. The biggest offenders are all functions
>> with
>> keyword arguments. In miniature, I think you can see this here:
>>
>> julia> function foo(X; thin=true)
>> svdfact(X)
>> end
>> foo (generic function with 1 method)
>>
>> # Before compiling this, let's make sure the work compiling foo isn't
>> hidden
>> # by other compilation needs:
>> julia> A = rand(3,3)
>> 3x3 Array{Float64,2}:
>> 0.57078 0.33557 0.56497
>> 0.0679035 0.944406 0.816098
>> 0.0922775 0.404697 0.0900726
>>
>> julia> svdfact(A)
>> Base.LinAlg.SVD{Float64,Float64,Array{Float64,2}}(3x3 Array{Float64,2}:
>> -0.507226 0.861331 0.0288001
>> -0.825227 -0.475789 -0.304344
>> -0.248438 -0.178138 0.952127 ,
>> [1.4844598265207638,0.5068781079827415,0.19995120630810712],3x3
>> Array{Float64,2}:
>> -0.248222 -0.707397 -0.661797
>> 0.873751 -0.458478 0.162348
>> 0.418264 0.537948 -0.731893)
>>
>> # OK, let's precompile foo
>> julia> @time precompile(foo, (Matrix{Float64},))
>> 0.000469 seconds (541 allocations: 35.650 KB)
>>
>> julia> @time foo(A)
>> 0.001174 seconds (18 allocations: 3.063 KB)
>> Base.LinAlg.SVD{Float64,Float64,Array{Float64,2}}(3x3 Array{Float64,2}:
>> -0.507226 0.861331 0.0288001
>> -0.825227 -0.475789 -0.304344
>> -0.248438 -0.178138 0.952127 ,
>> [1.4844598265207638,0.5068781079827415,0.19995120630810712],3x3
>> Array{Float64,2}:
>> -0.248222 -0.707397 -0.661797
>> 0.873751 -0.458478 0.162348
>> 0.418264 0.537948 -0.731893)
>>
>> # Note the 2nd call is 10x faster, despite precompilation
>> julia> @time foo(A)
>> 0.000164 seconds (18 allocations: 3.063 KB)
>> Base.LinAlg.SVD{Float64,Float64,Array{Float64,2}}(3x3 Array{Float64,2}:
>> -0.507226 0.861331 0.0288001
>> -0.825227 -0.475789 -0.304344
>> -0.248438 -0.178138 0.952127 ,
>> [1.4844598265207638,0.5068781079827415,0.19995120630810712],3x3
>> Array{Float64,2}:
>> -0.248222 -0.707397 -0.661797
>> 0.873751 -0.458478 0.162348
>> 0.418264 0.537948 -0.731893)
>>
>> # Note adding a keyword argument to the call causes a further 10x
>> slowdown...
>> julia> @time foo(A; thin=true)
>> 0.014787 seconds (3.36 k allocations: 166.622 KB)
>> Base.LinAlg.SVD{Float64,Float64,Array{Float64,2}}(3x3 Array{Float64,2}:
>> -0.507226 0.861331 0.0288001
>> -0.825227 -0.475789 -0.304344
>> -0.248438 -0.178138 0.952127 ,
>> [1.4844598265207638,0.5068781079827415,0.19995120630810712],3x3
>> Array{Float64,2}:
>> -0.248222 -0.707397 -0.661797
>> 0.873751 -0.458478 0.162348
>> 0.418264 0.537948 -0.731893)
>>
>> # ...but only for the first call
>> julia> @time foo(A; thin=true)
>> 0.000209 seconds (19 allocations: 3.141 KB)
>> Base.LinAlg.SVD{Float64,Float64,Array{Float64,2}}(3x3 Array{Float64,2}:
>> -0.507226 0.861331 0.0288001
>> -0.825227 -0.475789 -0.304344
>> -0.248438 -0.178138 0.952127 ,
>> [1.4844598265207638,0.5068781079827415,0.19995120630810712],3x3
>> Array{Float64,2}:
>> -0.248222 -0.707397 -0.661797
>> 0.873751 -0.458478 0.162348
>> 0.418264 0.537948 -0.731893)
>>
>>
>> Obviously the times here don't add up to much, but for a project the size
>> of
>> Gadfly it might matter.
>>
>> I should add that
>> precompile(foo, (Vector{Any}, Matrix{Float64}))
>> doesn't seem to do anything useful.
>>
>> Any ideas?
>>
>> Best,
>> --Tim
>>
>
