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DATE 2016-10-01

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MESSAGE
DATE 2016-10-31
FROM Ruben Safir
SUBJECT Re: [Learn] cuda kernels
From learn-bounces-at-nylxs.com Mon Oct 31 18:06:39 2016
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To: learn-at-nylxs.com
References: <9570d66b-7c02-4e2d-3225-20e008158f0d-at-mrbrklyn.com>
<87lgx48apw.fsf-at-contrapunctus.net>
From: Ruben Safir
Message-ID: <9195064a-00e1-19a4-cc27-d57f4cf82220-at-my.liu.edu>
Date: Mon, 31 Oct 2016 18:00:53 -0400
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Subject: Re: [Learn] cuda kernels
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On 10/31/2016 05:33 PM, Christopher League wrote:
> Ruben Safir ruben-at-mrbrklyn.com writes:
> =

> The video says that the below lines ask for 64 copys of the kernel
> on 64 threads? I don=92t see that
> =

> |cudaMemcpy(d_in, h_in, ARRAY_BYTES, cudaMemcpyHostToDevice);
> //launch kernel square<<<1, ARRAY_SIZE>>>(d_in, d_out);
> cudaMemcpy(h_out, d_out, ARRAY_BYTES, cudaMemcpyDeviceToHost);|
> =

> I don=92t really know anything about CUDA yet, but ARRAY_SIZE was 64. And
> this syntax: |square<<<1, ARRAY_SIZE>>>| is NOT valid C/C++ syntax. So I
> assume that the specialized GPU compiler interprets that in a way that
> it distributes the computation of the |square| function across 64 GPU
> threads=85?
> =

> BTW, I=92m pretty sure =93kernel=94 here doesn=92t refer to =93the Linux =
kernel.=94

No this is someones idea of how to teach parallel programming which is
to use a NVIDEO GPU and CUDA. WHy they couldn't come up with some idea
of what to call it other than "kernel" (maybe thread_instance or maybe a
closure ;) )

Actually, it is like a closure in that it is run through a thread with a
loop on each block? See the linked code for an example.

http://www.nylxs.com/docs/grad_school/parallel/src/cuda_second.c

ruben is me
let.me.in lets me in to most places

Maybe I am not understanding this yet. I promoised Samir I would catch
up with this class by Monday and it is Monday night. I need to do this
online class from udacity and UC Davis

I hate these video classes. I took one on Coursera for paelontology and
these things are watered down to the DUMBASS level. They talk to you
like your an idiot and they lull me to sleep. I'd give my right arm for
a textbook

https://www.udacity.com/course/intro-to-parallel-programming--cs344

These things are WORSE than the US Army video on venereal disease or how
to strip an M16.

It is killing me to do this and I'm not learning much for the time
spent. One thing that really is puzzling me is how memory is being
allocated and freed. See this line of code

cudaFree(d_out);
cudaMalloc(( void **) &d_out, ARRAY_BYTES );
cube<<<1, ARRAY_SIZE>>>(d_in, d_out);
cudaMemcpy(h_out, d_out, ARRAY_BYTES, cudaMemcpyDeviceToHost); //h_out
i s a static array. Can you memcpy like this?

for( int i =3D 0; i < ARRAY_SIZE; i++)
{
printf("Output =3D> %f ", h_out[i]);
}
//Free GPU
cudaFree(d_in);
cudaFree(d_out);


I'm trying to reuse an array for two different kernel calls and it dawns
on me, yah know, the are allocating dynamic memory to a built in
array... like WTF, can you do that?

Ruben

> =

> CL
> =

> =

> =

> _______________________________________________
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DRM is THEFT - We are the STAKEHOLDERS - RI Safir 2002
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