The timing for the Fortran code (using -Ofast) is
outer_func2 time = 0.160010 second.
I checked and it is using vector instructions. I'm impressed Julia is as
fast as Fortran in this case. I would have thought alias checking would
Julia down.
The Julia code is slow on release-0.5 as well as 0.6, so I will file an
issue.
Jared Crean
On Saturday, October 29, 2016 at 11:05:38 AM UTC-4, Jared Crean wrote:
>
> I noticed this morning that the loop are in the wrong order for a column
> major array. Reversing them, I get:
>
> testing outer_func
> 0.294904 seconds
> 0.296689 seconds
> testing outer_func2
> 0.280391 seconds
> 0.281223 seconds
>
> Now both versions have the phi instructions, so I guess that wasn't the
> problem
>
>
> And sprinkling a little @simd on the inner loops:
>
> testing outer_func
> 0.159910 seconds
> 0.157640 seconds
> testing outer_func2
> 0.151384 seconds
> 0.152224 seconds
>
> I'm going to write a Fortran code to do a performance comparison, but this
> is looking pretty good.
>
> Do you think I should file a performance issue for the original code?
>
> Jared Crean
>
>
>
> On Saturday, October 29, 2016 at 4:13:48 AM UTC-4, Kristoffer Carlsson
> wrote:
>>
>> Could it be some alias checking going on?
>>
>> Anyway, this code is horribly slow on 0.6 (even with #19097) it seems.
>>
>> to_indexes(::Int64, ::Int64, ::Vararg{Int64,N}) at operators.jl:868
>> (repeats 3 times)
>> kills performance.
>>
>>
>> On Saturday, October 29, 2016 at 5:56:12 AM UTC+2, Jared Crean wrote:
>>>
>>> I'm working on an high dimensional finite difference code, and I got a
>>> strange performance result. I have a kernel function that
>>> computes the stencil at a given point, and an outer function,
>>> outer_func, that loops over the dimensions and calls the kernel function at
>>> every grid point.
>>> I created a second function, outer_func2, with the same loops as
>>> outer_func, but rather than call the kernel function it has the contents of
>>> the kernel function copied into it. The source code is here:
>>> https://github.com/JaredCrean2/wave6d/blob/master/src/test_inline.jl
>>>
>>> The performance results (with bounds checking disabled and
>>> --math-mode=fast) are:
>>>
>>> testing outer_func
>>> 0.398586 seconds
>>> 0.398821 seconds
>>> testing outer_func2
>>> 2.522230 seconds
>>> 2.522479 seconds
>>>
>>>
>>>
>>> I ran this on in Intel Ivy Bridge (i7-3820) processor, using Julia 0.4.4
>>>
>>> I looked at the llvm code (attached), and noticed outer_func2 has a
>>> bunch of extra statements that look like
>>>
>>> %lsr.iv570 = phi i8* [ %scevgep571, %L21 ], [ %scevgep569, %L.preheader
>>> ]
>>>
>>>
>>>
>>> that are not present for outer_func. I don't know llvm code very well
>>> (hardly at all), so I'm not sure what these mean. Any help
>>> understanding either the llvm code or the performance difference would
>>> be appreciated.
>>>
>>>
>>>
>>> Thanks,
>>> Jared Crean
>>>
>>
