Nice. I'd say this is also "not bad" for the commercial solver :)
On Saturday, January 10, 2015 at 10:42:24 AM UTC+8, Petr Krysl wrote:
>
> Hello all,
>
> Big thanks to Tim Holy and Andreas Noack. The FE solver implemented in
> Julia as described previously (
> https://groups.google.com/forum/?f
Very good. is the url
https://github.com/PetrKryslUCSD/jfineale_for_trying_out still valid for
the new optimized version? may be you will release this as a package?
On Friday, 9 January 2015 21:42:24 UTC-5, Petr Krysl wrote:
>
> Hello all,
>
> Big thanks to Tim Holy and Andreas Noack. The FE so
Also documentation will be immesely helpful for mortals like me. I would
like to use this for optics problems
On Saturday, 10 January 2015 13:40:34 UTC-5, Zahirul ALAM wrote:
>
> Very good. is the url
> https://github.com/PetrKryslUCSD/jfineale_for_trying_out still valid for
> the new optimized
The optimized toolkit JFinEALE is now available on github:
https://github.com/PetrKryslUCSD/JFinEALE
Petr
Wow =)
Do you have more details about the commercial solver? Is it implemented in
C/C++?
If yes, this might become my favorite example to show off Julia's
strengths! Commercial C/C++ software looses against non commercial high
level code makes up a pretty good story =)
One thing I notice while
Hmm, not knowing a lot about this, just the keyword I have the question.
Is it possible to make it 3x faster yet and/or what hardware is that
benchmark obtained from?
Jeff,
Not sure this is answering your question: both the commercial software and
the Julia solver were run on the same machine (i7 with 16 GB of memory
running Windows 7).
On an equivalent Linux laptop the Julia solver is even faster. Comsol is
not available on that laptop.
P
On Saturday,
Simon,
The commercial solver was Comsol 4.4. I suppose it is implemented in C
or C++. Some of the user interface is probably in Java.
I will certainly consider your suggestion about the types. Frankly, I
didn't know better how to provide both type stability and flexibility.
Hopefully I wil
Correction: The repository has been now updated to look like a true Julia
package.
It can be cloned and there's even a rudimentary test.
https://github.com/PetrKryslUCSD/JFinEALE.jl
P
On Saturday, January 10, 2015 at 11:57:48 AM UTC-8, Petr Krysl wrote:
>
> The optimized toolkit JFinEALE is no
Le samedi 10 janvier 2015 à 18:10 -0800, Petr Krysl a écrit :
> Correction: The repository has been now updated to look like a true
> Julia package.
> It can be cloned and there's even a rudimentary test.
>
> https://github.com/PetrKryslUCSD/JFinEALE.jl
This sounds great. I was just wondering: ar
I'm not SURE, but the toolkit name (and the toolkit itself) is my
invention. First used in 2012.
This is not part of standard Matlab distribution
Petr
On Sunday, January 11, 2015 at 2:04:36 AM UTC-8, Milan Bouchet-Valat wrote:
>
> Le samedi 10 janvier 2015 à 18:10 -0800, Petr Krysl a
Le dimanche 11 janvier 2015 à 09:30 -0800, Petr Krysl a écrit :
> I'm not SURE, but the toolkit name (and the toolkit itself) is my
> invention. First used in 2012.
> This is not part of standard Matlab distribution
Ah, great. From my quick reading I thought that was a standard module.
N
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