Further update:
I made a c++ version[1] and see a similar effect (depending on
optimization levels) so it's not a julia issue (not that I think it
really was to begin with...).
The slow down is presented in the c++ version for all optimization
levels except Ofast and ffast-math. The julia
Le dimanche 12 juillet 2015 à 11:38 -0700, John Myles White a écrit :
http://julia.readthedocs.org/en/release-0.3/manual/performance-tips/
I don't think running the code in the global scope is the problem here:
most of the computing time is probably in BLAS anyway. I think MATLAB
uses Intel MKL
I think there's a big differences between developing core features in
packages and shipping them with the default version and having optional
third party packages implementing core features.
Like what, exactly? If the complaint is about ease of installation of
packages, then that's a known
We can probably pick a default, and it'll probably be Gadfly, but last I
checked Gadfly's support for running outside of IJulia is still a bit
lacking. To distribute a working version of IJulia you have to get into the
business of redistributing an entire Python installation, which could be
Hi,
I have Julia 0.3, Mongodb-osx-x86_64-3.0.4, and Mongo-c-driver-1.1.9
installed, but can't get Julia to access the Mongo Client through this
'untestable' package https://github.com/pzion/Mongo.jl, according to
http://pkg.julialang.org/.
I have tried Lytol/Mongo.jl and the command
On Sunday, July 12, 2015 at 4:47:42 PM UTC-4, Tony Kelman wrote:
The only thing I really would like to have
included by default it plotting tools, because they are so essential for
a lot of things.
I don't think you're going to find a single plotting tool that satisfies
everyone,
On Sun, Jul 12, 2015 at 8:31 PM, Kevin Owens kevin.j.ow...@gmail.com wrote:
I can't really help you debug the IR code, but I can at least say I'm seeing
a similar thing. It starts to slow down around just after 0.5, and doesn't
Thanks for the confirmation. At least I'm not crazy (or not the
Update:
I've just got an even simpler version without any complex numbers and
only has Float64. The two loops are as small as the following LLVM-IR
now and there's only simple arithmetics in the loop body.
```llvm
L9.preheader: ; preds = %L12,
I tried in in Matlab R2014a and Julia 0.3.10 on an 2.5 GHZ i5 and the
difference was much smaller:
22 seconds for Julia, 19 for Matlab
Also, I tried it in local and global scope and the difference wasn't more
than one or two seconds
El domingo, 12 de julio de 2015, 13:57:40 (UTC-5), Milan
Hi there,
I have very little experience with Julia and want to try whether it fits my
needs. I want to connect to a Neo4j database and send a Cypher statement
with Julia, see http://neo4j.com/docs/stable/cypher-intro-applications.html
.
The authorization works fine, but I could not manage to
I think the issue is you have the second argument (grant_type=client_
credentials) as the data for the post, and then the json=... argument
also as data for the post.
The API for post() is that it either takes the data as the second argument
to the function, or as a keyword argument data or a
In terms of dependencies and size, Gaston is probably minimal; it depends
on gnuplot only, which is a small binary and readily distributed on Linux,
OS X and windows. It offers basic features only (but has 3-D plotting), but
this may be an advantage for a default package. It is also well
Some of the slides are already available here. More should be posted
shortly.
http://juliatokyo.connpass.com/event/16570/presentation/
I few of them are in English. I noticed that more and more participates are
presenting using English slides despite the fact that the audience is near
100%
I can't really help you debug the IR code, but I can at least say I'm
seeing a similar thing. It starts to slow down around just after 0.5, and
doesn't get back to where it was at 0.5 until 0.87. Can you compare the IR
code when two different values are used, to see what's different? When I
On Sun, Jul 12, 2015 at 7:40 PM, Yichao Yu yyc1...@gmail.com wrote:
P.S. Given how strange this problem is for me, I would appreciate if
anyone can confirm either this is a real issue or I'm somehow being
crazy or stupid.
One additional strange property of this issue is that I used to have
I remember seeing this same performance gap before. I believe the problem
is that OpenBLAS doesn't have the correct thread defaults. Here are other
timings setting the threads directly:
*julia **blas_set_num_threads(1)*
*julia **@time eigfact(M);*
elapsed time: 1.827510669 seconds (79997048
Sorry, forgot the timing with the default number of threads.
*julia **@time eigfact(M);*
elapsed time: 2.261110895 seconds (79997048 bytes allocated, 2.05% gc time)
On Monday, July 13, 2015 at 10:19:33 AM UTC+10, Sheehan Olver wrote:
I remember seeing this same performance gap before. I
On Sun, Jul 12, 2015 at 10:30 PM, Yichao Yu yyc1...@gmail.com wrote:
Further update:
I made a c++ version[1] and see a similar effect (depending on
optimization levels) so it's not a julia issue (not that I think it
really was to begin with...).
After investigating the c++ version more, I
Hi,
On July 11th we had our 4th Julia meetup in Japan, JuliaTokyo #4. This
time we had 30+ perticipants.
---
JuliaTokyo #4 Presentation List in English
# Hands-on Session
by Michiaki Ariga
https://github.com/chezou/JuliaTokyoTutorial
(We tired to use JuliaBox, but failed with Maximum
As John and Matt said, a huge portion of the standard library is written in
Julia itself, so there's no real technical need for it to be developed
within the same repository. In fact developing technical features as
packages rather than as part of base allows getting features to users in a
I think there's a big differences between developing core features in
packages and shipping them with the default version and having optional
third party packages implementing core features.
Personally I also find the huge amount of packages to be slightly annoying,
but it's also clear the
It is worth differentiating what core Julia - the language and its standard
library - includes as a default, and what different distributions of Julia
may include to provide a good user experience. I personally have been
wanting to make a distribution that includes a few key packages that I
Please email julia...@googlegroups.com if you see such a timeout. Often it
just means that a new machine is booting up, and things should work in a
few minutes.
Sounds like a really fun meetup. BTW, are any of these slides in English -
and if so, are they available anywhere?
-viral
On
As someone who remembers the days of the first packages, I also want to throw
out the fact that the title of this issue should probably be viewed as a
triumph :-).
--Tim
On Sunday, July 12, 2015 10:59:10 AM Viral Shah wrote:
It is worth differentiating what core Julia - the language and its
Thank you!
I apparently just made a wrong assumption that Julia was a language for
scientific computing only. Once I think of it as a general purpose
language, the current structure makes total sense, just as it does for
python.
On Sunday, July 12, 2015 at 4:47:04 AM UTC-4, Tony Kelman
http://julia.readthedocs.org/en/release-0.3/manual/performance-tips/
On Sunday, July 12, 2015 at 8:33:56 PM UTC+2, Evgeni Bezus wrote:
Hi all,
I am a Julia novice and I am considering it as a potential alternative to
MATLAB.
My field is computational nanophotonics and the main numerical
Hello again,
I am writing to this post, as I face some more problems with trying to link
Julia functions with C++ code.
The thing is that I changed my current Julia version, I installed Julia
running the source code as I wanted
to install the Cxx package as well.
So, I just went to run the
Hi all,
I am a Julia novice and I am considering it as a potential alternative to
MATLAB.
My field is computational nanophotonics and the main numerical technique
that I use involves multiple solution of the eigenvalue/eigenvector problem
for dense matrices with size of about 1000*1000 (more
28 matches
Mail list logo
