I agree on the consistency part with other in-place operations. I certainly
don’t feel it’s hard to just use A_mul_B!, but my familiarity with BLAS
shouldn’t be taken for granted. And if an in-place operator syntax exists
in the language already…
How about the flip side of the argument, it appears
yes exactly !
On Wednesday, October 19, 2016 at 4:28:21 PM UTC+3:30, Milan Bouchet-Valat
wrote:
>
> Le mardi 18 octobre 2016 à 15:28 -0700, Steven G. Johnson a écrit :
> >
> >
> > > Since it uses the in-place assignment operator .= it could be made
> > > to work as desired, but there's some
Le mardi 18 octobre 2016 à 15:28 -0700, Steven G. Johnson a écrit :
>
>
> > Since it uses the in-place assignment operator .= it could be made
> > to work as desired, but there's some designing to do.
> >
>
> The problem is that it doesn't know that * is a matrix multiplication
> until compile-
On Tuesday, October 18, 2016 at 4:10:57 PM UTC-4, Stefan Karpinski wrote:
>
> Since it uses the in-place assignment operator .= it could be made to work
> as desired, but there's some designing to do.
>
The problem is that it doesn't know that * is a matrix multiplication until
compile-time.
Since it uses the in-place assignment operator .= it could be made to work
as desired, but there's some designing to do.
On Tue, Oct 18, 2016 at 2:55 PM, Cameron McBride
wrote:
> You mean like the following?
>
> julia> A=[1.0 2.0; 3.0 4.0]; B=[1.0 1.0; 1.0 1.0]; Y = similar(B); Y.= A *
> B
>
> T
You mean like the following?
julia> A=[1.0 2.0; 3.0 4.0]; B=[1.0 1.0; 1.0 1.0]; Y = similar(B); Y.= A * B
This doesn’t work as you might hope. I believe it just creates a temporary
result of A*B and then stuffs it into the preexisting Y.
On Tue, Oct 18, 2016 at 2:41 PM, Jérémy Béjanin
wrote:
>
I know, I was asking about that being the default behaviour of *
On Tuesday, October 18, 2016 at 2:10:14 PM UTC-4, Stefan Karpinski wrote:
>
> That's what A_mul_B! does.
>
> On Tue, Oct 18, 2016 at 1:45 PM, Jérémy Béjanin > wrote:
>
>> I think this is something I might have read about in the past
That's what A_mul_B! does.
On Tue, Oct 18, 2016 at 1:45 PM, Jérémy Béjanin
wrote:
> I think this is something I might have read about in the past, but are
> there plans to make y = a*b use an already allocated y?
>
> On Tuesday, October 18, 2016 at 12:38:00 PM UTC-4, Stefan Karpinski wrote:
>>
>
I think this is something I might have read about in the past, but are
there plans to make y = a*b use an already allocated y?
On Tuesday, October 18, 2016 at 12:38:00 PM UTC-4, Stefan Karpinski wrote:
>
> A_mul_B!(Y, A, B) -> Y
>
> Calculates the matrix-matrix or matrix-vector product A⋅B an
A_mul_B!(Y, A, B) -> Y
Calculates the matrix-matrix or matrix-vector product A⋅B and stores the
result in Y, overwriting the
existing value of Y. Note that Y must not be aliased with either A or B.
julia> A=[1.0 2.0; 3.0 4.0]; B=[1.0 1.0; 1.0 1.0]; Y = similar(B);
A_mul_B!(Y, A, B);
ju
hi guys
is there a way to reduce allocated memory in matrix multiplications?
for example this code blew in my machine gives :
function test4(n)
a = rand(n,n)
for i = 1:100
a*a
end
end
-- answer --
test4(1)
# force compiling
@time test4(100
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