You are right. My previous timings were totally wrong anyway, due to a bug
I introduced into my program. After fixing it, a fair comparison shows that:
Base.:+{N}(a::NTuple{N}, b::NTuple{N}) = ntuple(i -> a[i] + b[i], Val{N})
is exactly the same speed as the recursive functions I was using. And it is
at least 20% faster in my application than the version with N instead of
Val{N}.
Unfortunately, in my application, the other solution:
((a[i] + b[i] for i = 1:N)...)
is extremely slow, and in fact Julia crashes with a segfault before my
benchmark finishes (due to using too much memory). So that isn't an option.
Anyway, the first solution above is as fast as what I had, and much more
convenient. I will go with that for now.
Bill.
On 10 August 2016 at 18:17, Shashi Gowda <shashigowd...@gmail.com> wrote:
>
> Base.:+{N}(a::NTuple{N}, b::NTuple{N}) = ntuple(i -> a[i] + b[i], Val{N})
>
> should be slightly faster and should not allocate unlike
>
> Base.:+{N}(a::NTuple{N}, b::NTuple{N}) = ntuple(i -> a[i] + b[i], N)
>
>
> On Wed, Aug 10, 2016 at 8:36 PM, 'Bill Hart' via julia-users <
> julia-users@googlegroups.com> wrote:
>
>> This code seems to be (about 50%) faster than recursive functions:
>>
>> Base.:+{N}(a::NTuple{N}, b::NTuple{N}) = ntuple(i -> a[i] + b[i], N)
>>
>>
>> But this seems (about 50%) slower:
>>
>> ((a[i] + b[i] for i = 1:N)...)
>>
>>
>> Anyway, I can use the first method, until I find something faster. It's
>> definitely way more convenient. Thanks.
>>
>> Bill.
>>
>>
>>
>> On 10 August 2016 at 16:56, Erik Schnetter <schnet...@gmail.com> wrote:
>>
>>> The built-in type `CartesianIndex` supports adding and subtracting, and
>>> presumably also multiplication. It is implemented very efficiently, based
>>> on tuples.
>>>
>>> Otherwise, to generate efficient code, you might have to make use of
>>> "generated functions". These are similar to macros, but they know about the
>>> types upon which they act, and thus know the value of `N`. This is a bit
>>> low-level, so I'd use this only if (a) there is not other package
>>> available, and (b) you have examined Julia's performance and found it
>>> lacking.
>>>
>>> I would avoid overloading operators for `NTuple`, and instead us a new
>>> immutable type, since overloading operations for Julia's tuples can have
>>> unintended side effects.
>>>
>>> -erik
>>>
>>>
>>> On Wed, Aug 10, 2016 at 9:57 AM, 'Bill Hart' via julia-users <
>>> julia-users@googlegroups.com> wrote:
>>>
>>>> Does anyone know an efficient way to add NTuples in Julia?
>>>>
>>>> I can do it using recursive functions, but for various reasons this is
>>>> not efficient in my context. I really miss something like tuple(a[i] + b[i]
>>>> for i in 1:N) to create the resulting tuple all in one go (here a and b
>>>> would be tuples).
>>>>
>>>> The compiler doesn't do badly with recursive functions for handling
>>>> tuples in very straightforward situations, but for example, if I want to
>>>> create an immutable type based on a tuple the compiler doesn't seem to be
>>>> able to handle the necessary optimisations. At least, that is what I infer
>>>> from the timings. Consider
>>>>
>>>> immutable bill{N}
>>>> d::NTuple{N, Int}
>>>> end
>>>>
>>>> and I want to add two bill's together. If I have to add the tuples
>>>> themselves using recursive functions, then I no longer seem to be able to
>>>> do something like:
>>>>
>>>> A[i] = B[i] + C[i] efficiently, where A, B and C are arrays whose
>>>> elements are of type bill.
>>>>
>>>> I know how to handle tuples via arrays, but for efficiency reasons I
>>>> certainly don't want to do that, e.g. tuple([a[i] + b[i] for i in 1:N]...).
>>>>
>>>> Bill.
>>>>
>>>
>>>
>>>
>>> --
>>> Erik Schnetter <schnet...@gmail.com> http://www.perimeterinstitute.
>>> ca/personal/eschnetter/
>>>
>>
>>
>
