A great tool to figuring out what is going on in these cases is
`@code_llvm`. It shows you a representation of your code that is still
readable, but very close to the machine.
Your simple julia code without a `@simd` is nearly optimal, but does
benefits from the inclusion of `@inbounds`
- While_loop with `@inbounds`: minimum time: 797.28 μs
- While loop without `@inbounds`: minimum time: 1.01 ms
- For loop without & with `@inbounds`: minimum time: 802/812.11 μs
function simple(A, b, stride, N)
N = min(N, length(A))
for i in 1:stride:N
@inbounds A[i] *= b
end
end
function while_based(A, b, stride, N)
i = 1
N = min(N, length(A))
while i <= N
A[i] *= b
i += stride
end
end
Now to the question whether or not `@simd` is beneficial in this case. LLVM
has a loop vectorizer that we run and it has a cost-benefits (and
correctness) analysis when it sees a loop. The fact that in the code_llvm
we don't see vectorized code means that LLVM did not deem it worth while to
vectorize our code (as Kristoffer said most likely because of non unit
strides). With `@simd` we (forcibly) tell LLVM to vectorize out code and to
be less strict about correctness and to also not to do a cost-benefit
analysis. While vectorized code has great performance benefits it also
comes with costs (code size increase, overhead).
I hope this tough analysis helps.
On Friday, 29 July 2016 22:36:50 UTC+9, Kristoffer Carlsson wrote:
>
> It is likely because the ranges are not UnitRanges.
>
> On Friday, July 29, 2016 at 5:35:57 AM UTC-4, Andreas Lobinger wrote:
>>
>> Hello colleague,
>>
>> On Friday, July 29, 2016 at 8:59:36 AM UTC+2, Juan Lopez wrote:
>>>
>>> Hello,
>>>
>>> I have a function which is doing basically an operation inside a loop
>>> and when adding @simd or @inbounds time doesn't improve, in any case it
>>> seems slightly worse.
>>>
>>
>>
>>> Is there an explanation for this? Thank you
>>>
>>
>> there is a non-vanishing propability, that the plain loop is already
>> compiled to the optimal code. Maybe you try to look at the lowered code.
>>
>>
>>
>
