That is definitely true. Of course, we musicians need it more than most
computer users out there...
On 2/24/2016 11:57 AM, Jonathan Wilkes wrote:
I'd say a solution would deserve the nobel prize in computers. :)
-Jonathan
On Wednesday, February 24, 2016 11:40 AM, david medine
<[email protected]> wrote:
Reading a full inbox in a non-parallelized fashion leads to cross
posting. Sorry for the repost, but this belongs on this thread.
Yeah, but the problem here (automatic compute resource distribution)
isn't just with the actual distribution. Control timing is a huge
issue too. If you have multiple voices of the same synth on different
threads, good luck playing a chord. It will frequently be an arpeggio.
If there are very strict, predictable rules about the order of when
each voice computes and when it sleeps in order to wait for new
samples and control signals, this problem vanishes, but then you are
no longer computing in parallel, and you might as well have everything
on one thread anyway.
This is a /really/ interesting problem. If someone can solve it, she
deserves the nobel prize in computer music.
On 2/24/16 5:59 AM, Christof Ressi wrote:
Another possibility for at least some degree of parallel audio processing, I guess, is to
use streaming objects + several instances of Pd. I tried out [udpsend~] and
[udpreceive~] (taken from the "net" library in Pd extended) and they seem to
work reliably. Of course there is some latency envolved and it's no practical solution
for our future 100 core machines :-p.
What are in your experience the best methods for sharing audio via different Pd
instances?
And does anyone know the current status of "Audio over OSC"? I found this paper from 2010http://iem.kug.ac.at/fileadmin/media/iem/projects/2010/jaeger.pdf
Christof
Gesendet: Mittwoch, 24. Februar 2016 um 11:12 Uhr
Von: Jack<[email protected]> <mailto:[email protected]>
An:[email protected] <mailto:[email protected]>
Betreff: Re: [PD] How's Pd limited?
Hello,
Le 24/02/2016 00:19, Matt Barber a écrit :
Can anyone explain more why [pd~] doesn't fulfill the desire for
parallel processing, and maybe provide an example of something outside
of Pd that does? I don't feel like I have a great handle on the design.
As Jonathan said, it seems like Pd's determinism constraint is a big
hurdle to clear, though it's already relaxed a bit with netsend/receive.
What are the main differences between running an instance of Pd as a
[pd~] slave to another instance, and running two instances that
communicate via netsend/receive and jack?
I think, the main difference is :
- with [pd~] your communication is synchronous
- with [netsend]/[netreceive] your communication is asynchronous
So (if i am right), if something is heavy to compute (more than 100% of
your CPU) in your subprocess with [pd~], your parent have to wait the
end of this computation. This is not the case with [netsend]/[netreceive].
++
Jack
On Tue, Feb 23, 2016 at 5:45 PM, David Medine <[email protected]
<mailto:[email protected]>
<mailto:[email protected]> <mailto:[email protected]>> wrote:
I think we all need to learn more about multi-threading if we want
to run real-time, modular, digital signal processing algorithms on
multi-core machines. I, for one, can not think of any general,
robust way to do this. In that sense, Pd's adherence to single
threading is actually a very elegant solution to the problem.
On 2/23/2016 12:25 PM, martin brinkmann wrote:
On 22/02/16 02:49, Matti Viljamaa wrote:
How do you think Pure Data is limited?
for me the only real and important (i can think of at the
moment) limitation is the block-based audio processing.
to me this seems quite unnatural and inconvenient when dealing with
digital audio. it kept me for a couple of years from using pd,
though it
is only a 'showstopper' in rather few cases, i found out.
feedback in large/complex patches for example, since it
is not very practical (or possible at all) to re-block
everything to 1...
what i tried but couldn't (yet): build a decent piano-roll
editor (vanilla).
and i believe too, pd has to 'learn' better multithreading to run
adequately on our future machines with hundreds or even thousands of
arm-cores...
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