Indeed, looks like a potential performance regression in 0.3 for sumofsins2:
function sumofsins2(n::Integer)
r = 0.0
for i in 1:n
r += sin(3.4)
end
return r
end
— John
On Aug 24, 2014, at 5:06 PM, Mohammed El-Beltagy <[email protected]>
wrote:
> That is no longer valid under in Julia 0.3. The code only runs 3x faster and
> the type stable code looks a bit more complex.
>
> On Monday, December 16, 2013 8:48:40 PM UTC+2, John Myles White wrote:
> I think Michael is suggesting that it would help to have an automated tool to
> do this. This stuff comes up in subtle ways in complex code. While editing
> some of the t-SNE code someone posted recently, I found that just removing a
> single type-unstable call to maximum made the code 100x faster. It was a bit
> too complex to read through code_typed or anything else, so automated tools
> would make a big difference.
>
> -- John
>
> On Dec 16, 2013, at 10:46 AM, Ivar Nesje <[email protected]> wrote:
>
>> You might use code_typed and look at the output and see if it looks curious.
>>
>> kl. 19:28:05 UTC+1 mandag 16. desember 2013 skrev John Myles White følgende:
>> I believe Leah was working on a tool to do some of this.
>>
>> -- John
>>
>> On Dec 16, 2013, at 10:22 AM, Michael Fox <[email protected]> wrote:
>>
>> > After reading about type stability in the FAQ and this excellent post --
>> > http://www.johnmyleswhite.com/notebook/2013/12/06/writing-type-stable-code-in-julia/
>> > -- I want to make sure I'm doing it right.
>> >
>> > Is there any way to ask Julia if a particular function has achieved type
>> > stability? This would be a good feature for julialint.
>>
>
