Also Raghu’s write up was about taking the wikipedia looping pseudo-code for
matrix multiplication
and thinking in array languages on how to implement. I thought the solution in
K was rather elegant
and wondered what matrix multiplication from scratch would look like in J using
Raghu’s K
I missed that. I think this is an elegant way that avoids explicit rank.
On Tue, Jul 19, 2022 at 2:13 PM Hauke Rehr wrote:
> Tom did, in the very post starting this thread:
>
> (1+i. 4 3) +/ . * 1+i. 3 4
> 38 44 50 56
> 83 98 113 128
> 128 152 176 200
> 173 206 239 272
>
> Am
Tom did, in the very post starting this thread:
(1+i. 4 3) +/ . * 1+i. 3 4
38 44 50 56
83 98 113 128
128 152 176 200
173 206 239 272
Am 19.07.22 um 20:10 schrieb Devon McCormick:
I'm puzzled why no one has used the basic matrix multiplication expression
in J.
matmul3
([: +/ *)"1
I'm puzzled why no one has used the basic matrix multiplication expression
in J.
matmul3
([: +/ *)"1 _
mat1=. <.0.5+10*<:+:1000 1000?@$0
mat0=. <.0.5+10*<:+:1000 1000?@$0
(10) 6!:2 'mat0 matmul3 mat1'
0.737084
(10) 6!:2 'mat0 +/ . * mat1'
0.0499271
(mat0 matmul3 mat1) -: mat0 +/
My late night laziness and I got bitten by the 13 : definition doesn’t always
work
correctly with both x and y variables. Which I just assumed was working
correctly.
Now when I fix the definition of matmul3 so it works correctly (as Elijah
pointed out) the variable
representation does not
On Tue, 19 Jul 2022, Thomas McGuire wrote:
Now the wierd thing is the timing for matmul3 is slow on par with emulating K
matrices in J
But if I use the fork directly it is as fast as Raul’s solution
You are measuring two completely different things.
10 timex'bmat1 ([: +/ *)"1 _ bmat2'
I had a chance to digest the K-way of lists of a list method Raul presented in
J.
After I understood it somewhat and its use of the leaf operator. I was curious
as
how fast these things ran, as implied by Raghu and Raul it was fairly slow
compared to
the J matrix implementation proposed by
https://gist.github.com/chrispsn/af6844b80687462814fc39d4b97399a6
may be of interest
On Wed, 13 Jul 2022, Raul Miller wrote:
On Wed, Jul 13, 2022 at 4:23 AM Razetime wrote:
The ngn/k version is much better for the K array model, and it's intended
as a nice and short description of the
On Wed, Jul 13, 2022 at 4:23 AM Razetime wrote:
> The ngn/k version is much better for the K array model, and it's intended
> as a nice and short description of the algorithm for nested lists.
Oh... yes... K is highly optimized for nested rank 1 lists of rank 1
lists -- J... not so much. J's
Hi, I wrote the original essay.
The ngn/k version is much better for the K array model, and it's intended
as a nice and short description of the algorithm for nested lists.
Your translation looks correct, and you might get a one-to-one translation
with boxed arrays and table. J doesn't really
I have to question the use of 'elegant' here.
Matrix multiplication has a similarly short representation in J. But the
actual code: it breaks the operation into several layers of loops: one
sized to the registers, one sized to D1$, one sized to D2$.
Simply following the definition of the
Well... of course, you can express matrix multiplication *using* rank:
(1+i.4 3) +/@:*"1 _(1+i.3 4)
38 44 50 56
83 98 113 128
128 152 176 200
173 206 239 272
And, conceptually, all verbs in J have rank, so that always gets used.
But, I guess you are asking how to avoid the rank
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