[julia-users] Re: Julia code 5x to 30x slower than Matlab code

> > I hope to have a release version in about a month, which is the estimated > time for releasing GMT5.2. There are still several issues from the GMT side > but overall most of it works already. Feel free to test it (see the > gallery.jl for several usage examples) but note that you'll have

[julia-users] Re: Julia code 5x to 30x slower than Matlab code

Yes, we will be releasing Win binaries when it's released. It's for the mean time that interested people needs to build from source. domingo, 27 de Setembro de 2015 às 14:50:25 UTC+1, Marcio Sales escreveu: > > I hope to have a release version in about a month, which is the estimated >> time

[julia-users] Re: Julia code 5x to 30x slower than Matlab code

sexta-feira, 25 de Setembro de 2015 às 14:47:49 UTC+1, Marcio Sales escreveu: > > all right... Well.. Julia's price will allways be better... > Btw.. what about crowdfunded initiatives? Has anyone tried that? I would > be wiling to donate for a geospatial visualization package, for example...

[julia-users] Re: Julia code 5x to 30x slower than Matlab code

This just came to while I remembered that Matlab is so expensive.. I never did this myself, but heard that Openstreetmaps, for example, was/is crowdsourced, so why not trying it for Julia development?

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

+1 Someone give this man a cookie. On 25 September 2015 at 01:46, Steven G. Johnson wrote: > To put it another way, there are plenty of problems that can't be > vectorized effectively. ODEs, matrix assembly for FEM or BEM, implementing > special functions... If you do

[julia-users] Re: Julia code 5x to 30x slower than Matlab code

Although not understanding the final part of the performance tips, I would like to make the point here that the "style guide" could also use some love. I am too obsessive to aesthetic. I cannot accept to write ugly code. On Thursday, September 24, 2015 at 10:13:18 PM UTC+2, Steven G.

[julia-users] Re: Julia code 5x to 30x slower than Matlab code

all right... Well.. Julia's price will allways be better... Btw.. what about crowdfunded initiatives? Has anyone tried that? I would be wiling to donate for a geospatial visualization package, for example...

[julia-users] Re: Julia code 5x to 30x slower than Matlab code

Then don't?

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

Marcio: crowdfunded julia packages is a really awesome idea... is there a platform for this already for other languages? or should we create one? On Fri, Sep 25, 2015 at 9:47 AM, Marcio Sales wrote: > all right... Well.. Julia's price will allways be better... > Btw..

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

> Marcio: crowdfunded julia packages is a really awesome idea... is there a > platform for this already for other languages? or should we create one? > > On Fri, Sep 25, 2015 at 9:47 AM, Marcio Sales > wrote: > >> all right... Well.. Julia's price will allways be

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

[This (part A) is probably not implemented yet, and probably not even a new idea.. possibly julia-dev material?] On mið 23.sep 2015 16:26, Milan Bouchet-Valat wrote: Le mercredi 23 septembre 2015 à 07:38 -0700, Páll Haraldsson a écrit : instead of these two type-unstable variants: type

[julia-users] Re: Julia code 5x to 30x slower than Matlab code

Wow. All this discussion to make Julia only *as fast as* the old scripting languages? I gotta say that worried me a bit. What do you do when there's no code to compare? How will you know that it was really a good idea switching from Matlab/Python to Julia? Considering what the develops

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

I have been spending the past weeks trying to really understand how to implement efficient code. As far as I can tell (from first hand experience), Julia really does give you a prominent edge over R and Matlab in terms of performance. However, I also think that there are currently a lot of

[julia-users] Re: Julia code 5x to 30x slower than Matlab code

There is no question that Julia needs more work. This applies to offering speedy primitives and also doing more optimizations. But I think you get one thing wrong. The magic lays in the fact, that in Julia you have the chance to write the vectorized implementation that are offered by languages

[julia-users] Re: Julia code 5x to 30x slower than Matlab code

On Thursday, September 24, 2015 at 12:17:25 PM UTC, Marcio Sales wrote: > > Wow. All this discussion to make Julia only *as fast as* the old > scripting languages? > This is not what I meant. Matching C is the goal I understand and often that goal is met. *Should* always be possible. A. By

[julia-users] Re: Julia code 5x to 30x slower than Matlab code

"Idiot-proof" sounds awesome, but at least makes it so that the user could be aggressive to the language, and not the language to be aggressive to the newbie, would be a great to way to approach. It would also help avoinding "scarecrowing" away potential contributors.

[julia-users] Re: Julia code 5x to 30x slower than Matlab code

Yeah cause Haskell is so super newbie friendly??? I don't think the developers had the goal with Julia that you should be able to write code with as few characters as possible. On Thursday, September 24, 2015 at 5:54:37 PM UTC+2, Páll Haraldsson wrote: > > On Thursday, September 24, 2015 at

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

I think julia is very newbie-friendly, except for some very common patterns that people run into. How many times do people run into the "globals are slow" problem, post a long question about why "I thought julia was fast...", and then we go through the same performance tips. It would be nice if

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

My argument does be purely about performance. However, you won't know if your Julia code is 1.3x slower than C or 130x slower, until you write the C code. On Thursday, September 24, 2015 at 7:14:46 PM UTC+2, Tom Breloff wrote: > > Unless you are experts of compilers and Julia language, you can

[julia-users] Re: Julia code 5x to 30x slower than Matlab code

On Thursday, September 24, 2015 at 1:55:18 PM UTC-4, Sisyphuss wrote: > > However, Julia is assumed to be fast (high expectation), and performance > varies a lot according to the knowledge/skill a programmer own (high > variance). > Again, that's true in any language where you are trying to

[julia-users] Re: Julia code 5x to 30x slower than Matlab code

Rewriting code in another language, unless it affords supports some manner of proof and validation, is not a good approach to proving Julia code operates as designed and intended. There is a likelihood of doing something not quite right twice or two different things differently. Sometimes, I

[julia-users] Re: Julia code 5x to 30x slower than Matlab code

> > it would be nice to have a more obvious way to automatically fix things > like globals that could be declared const, or maybe even automatically > wrapping global code in functions? I think these words reflect exactly the point I wanted to make. I understand the grandiosity that is

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

On 24 September 2015 at 14:17, Marcio Sales wrote: > Wow. All this discussion to make Julia only *as fast as* the old > scripting languages? I gotta say that worried me a bit. What do you do when > there's no code to compare? How will you know that it was really a good >

[julia-users] Re: Julia code 5x to 30x slower than Matlab code

These criticisms are frankly ridiculous. When your critique could be applied to any programming language that exists then you are doing it wrong.

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

On 24 September 2015 at 22:00, Marcio Sales wrote: > it would be nice to have a more obvious way to automatically fix things >> like globals that could be declared const, or maybe even automatically >> wrapping global code in functions? > > > I think these words reflect

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

On 24 September 2015 at 22:31, Marcio Sales wrote: > Matlab *requires* vectorized code because Matlab loops are very slow by >> comparison >> > It is much faster these days (from R2014). > It is much faster than it used to be, but it is still slow. I know that Matlab

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

On 24 September 2015 at 19:00, Sisyphuss wrote: > What do you do when there's no code to compare? >> > This is a good point! When I write a piece of Julia code, how do I know I > wrote it correctly? Should I write a C version to prove it? > This is what I called the risk

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

This conversation is getting pretty tiresome. There are programs where Matlab is already as fast as it's possible to be. If all you're doing is computing a big matrix product, for example, then all any language is just going to call BLAS. Julia is not going to be any faster than Matlab for that,

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

Le jeudi 24 septembre 2015 à 13:31 -0700, Marcio Sales a écrit : > > Matlab *requires* vectorized code because Matlab loops are very > > slow by comparison > It is much faster these days (from R2014). I remember I ran some very > simple comparisons and it surprised me that Matlab ran a bit faster

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

+1 On Thu, Sep 24, 2015 at 5:28 PM, Stefan Karpinski wrote: > This conversation is getting pretty tiresome. There are programs where > Matlab is already as fast as it's possible to be. If all you're doing is > computing a big matrix product, for example, then all any

[julia-users] Re: Julia code 5x to 30x slower than Matlab code

To put it another way, there are plenty of problems that can't be vectorized effectively. ODEs, matrix assembly for FEM or BEM, implementing special functions... If you do enough scientific computing, eventually you will hit a problem where you need to write your own inner loops, and then with

[julia-users] Re: Julia code 5x to 30x slower than Matlab code

> > That is a meaningless comparison. First, you are not comparing loops, you > are comparing matrix inversion. Second, neither Matlab nor Julia will > natively perform a matrix inversion well. They are both going to use an > external library (LAPACK) so what you are testing is the library,

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

On 24 September 2015 at 14:47, Christof Stocker wrote: > As far as I can tell (from first hand experience), Julia really does give > you a prominent edge over R and Matlab in terms of performance. However, I > also think that there are currently a lot of ways to shoot

[julia-users] Re: Julia code 5x to 30x slower than Matlab code

> > Matlab *requires* vectorized code because Matlab loops are very slow by > comparison > It is much faster these days (from R2014). I remember I ran some very simple comparisons and it surprised me that Matlab ran a bit faster than Julia in a for loop of matrices multiplications and

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

On 24 September 2015 at 19:55, Sisyphuss wrote: > People won't apply my critique on Matlab or R, because these languages are > assumed to be slow and they must be slow. So there is no "risk/variance" > (in the good sense) for these language. No sooner one learns to write

[julia-users] Re: Julia code 5x to 30x slower than Matlab code

> > What do you do when there's no code to compare? > This is a good point! When I write a piece of Julia code, how do I know I wrote it correctly? Should I write a C version to prove it? This is what I called the risk to write Julia code. Unless you are experts of compilers and Julia language,

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

> > Unless you are experts of compilers and Julia language, you can never know > whether your code give you an edge or not Isn't this true of all languages? How do you know you did that C pointer arithmetic correctly? Or that python didn't silently clobber your data? This is why integration

[julia-users] Re: Julia code 5x to 30x slower than Matlab code

People won't apply my critique on Matlab or R, because these languages are assumed to be slow and they must be slow. So there is no "risk/variance" (in the good sense) for these language. No sooner one learns to write vectorized code, than he reaches the limit of these languages. However,

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

On Monday, September 21, 2015 at 12:18:12 AM UTC, Daniel Carrera wrote: > > > On 21 September 2015 at 01:36, Páll Haraldsson > wrote: > >> I know about @devec but wander how close Julia is also able to match the >> speed of its looks with more condensed code or

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

Le mercredi 23 septembre 2015 à 05:15 -0700, Páll Haraldsson a écrit : > > > On Monday, September 21, 2015 at 12:18:12 AM UTC, Daniel Carrera > wrote: > > > > On 21 September 2015 at 01:36, Páll Haraldsson < > > pall.ha...@gmail.com> wrote: > > > I know about @devec but wander how close Julia

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

On 23 September 2015 at 16:38, Páll Haraldsson wrote: > Yes, > > What prompted my question was Tim Holy: "String is not a concrete type. > Consider ASCIIString or UTF8String." Maybe ok in this case. If he meant it > as a general advise, > This is not advice. Tim was

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

On 23 September 2015 at 14:15, Páll Haraldsson wrote: > > On Monday, September 21, 2015 at 12:18:12 AM UTC, Daniel Carrera wrote: >> >> >> On 21 September 2015 at 01:36, Páll Haraldsson >> wrote: >> >>> I know about @devec but wander how close

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

Yes, What prompted my question was Tim Holy: "String is not a concrete type. Consider ASCIIString or UTF8String." Maybe ok in this case. If he meant it as a general advise, I thought maybe a Union of the UTF encodings (and ASCII?) would be needed to be general. Or not, as you say (and I), this

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

Le mercredi 23 septembre 2015 à 07:38 -0700, Páll Haraldsson a écrit : > Yes, > > What prompted my question was Tim Holy: "String is not a concrete > type. Consider ASCIIString or UTF8String." Maybe ok in this case. If > he meant it as a general advise, I thought maybe a Union of the UTF >

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

On mið 23.sep 2015 15:34, Daniel Carrera wrote: To match MATLAB in speed, Julia code should typically be about the same length. That is good enough for me (to match MATLAB and Python's length and at least not be slower) and then no big concern there. C/C++ doesn't even have real macros, and

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

On 23 September 2015 at 20:21, Páll Haraldsson wrote: > Between API calls. "second class platform" was probably too strong a > language. I'm not sure if UTF8 is preferred anywhere in Julia (in Base). I honestly don't know if UTF8 is preferred. I have never heard

[julia-users] Re: Julia code 5x to 30x slower than Matlab code

The biggest problem seems to be the main loop in calc_net.jl: for idx = 1:numO o = o_vec[idx] # conditions in which something occurs cond_A_su = (o .< b_hist[:,3]) & (b_hist[:,1] .== 65) cond_B_su = (o .> b_hist[:,3]) & (b_hist[:,1] .== 66) # conditions in which something

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

Did you run the code twice to not time the JIT compiler? For me, my version runs in 0.24 and Daniels in 0.34. Anyway, adding this to Daniels version: https://gist.github.com/KristofferC/c19c0ccd867fe44700bd makes it run in 0.13 seconds for me. On Sunday, September 20, 2015 at 7:28:09 PM

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

That might make a difference because there is a lot of performance improvements on 0.4 (most notably the new garbage collector). PyPlot works fine for me on 0.4 btw. On Sunday, September 20, 2015 at 8:29:52 PM UTC+2, Daniel Carrera wrote: > > Thanks. > > No, I'm not on 0.4 yet. I thought it

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

Thanks. No, I'm not on 0.4 yet. I thought it wasn't stable (and I think PyPlot doesn't work on it yet). I'm on 0.3.11. On 20 September 2015 at 20:28, Kristoffer Carlsson wrote: > https://github.com/timholy/ProfileView.jl is invaluable for performance > tweaking. > > Are

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

As an interim step, you can also get text profiling information using Profile.print() if the graphics aren't working. On Sunday, September 20, 2015 at 11:35:35 AM UTC-7, Daniel Carrera wrote: > > Hmm... ProfileView gives me an error: > > ERROR: panzoom not defined > in view at

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

> As an interim step, you can also get text profiling information using > Profile.print() if the graphics aren't working. You could also try https://github.com/mauro3/ProfileFile.jl which writes the profile numbers into a file *.pro. Similar to the memory and coverage files. > On Sunday,

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

Whoo hoo! It looks like I got another ~6x or ~7x improvement. Using Profile.print() I found that the hottest parts of the code appeared to be the if-conditions, such as: if o < b_hist[j,3] It occurred to me that this could be due to cache misses, so I rewrote the code to store the data

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

I just added the 'sim' variable to the outer scope and a return value. This incurs a small speed penalty. I also removed the remaining `reshape()` from calc_net and that produced a small speed improvements. The two changes roughly cancel out. On my computer I measure a 3% net improvement, which is

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

Adding your loop increased performance by another 20%. Good stuff! Changes uploaded to Github. Cheers, Daniel. On 20 September 2015 at 23:13, Kristoffer Carlsson wrote: > For me, your latest changes made the time go from 0.13 -> 0.11. It is > strange we have so different

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

Ah ja @code_warntype is in Julia v0.4. I thin in 0.3 you could just do @code_type and look for ::Any See the introduction PR https://github.com/JuliaLang/julia/pull/9349 On Sunday, 20 September 2015 23:49:55 UTC+9, Daniel Carrera wrote: > > Uhmm... I get an error: > > ERROR: @code_warntype not

[julia-users] Re: Julia code 5x to 30x slower than Matlab code

Daniel, you are still using a Dict of params, which kills type inference. Pass parameters directly or put them in (typed) fields of a composite type. (On the other hand, common misconception: there is no performance need to declare the types of function arguments.)

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

Thanks for the several comments and Daniel for the alternate versions of the calc_net function! Viral, unfortunately I'm not a GitHub/version control user (yet), but I've copied the code into a gist here: https://gist.github.com/anonymous/cee196ee43cb9bf1c8b6. The code can be run by running

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

Whoo hoo! After replacing all the Dict's with appropriate composite types, I got an additional ~4x speed improvement. Combined with my previous work, the code is now 30x faster than the original. So now Julia should at least match Matlab. I uploaded the modified code to GitHub:

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

On 20 September 2015 at 17:08, Adam wrote: > Daniel, can you clarify your comment of "the first two lines require > memory allocation and might also have a bad memory profile"? I'm not sure > if it's addressed in this latest gist or not. > I don't know how much you know

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

The biggest problem right now is that Prob_o is global in calc_net. You need to pass it as an argument too. It's one of the drawback of having everything global by default, this kind of mistakes are sometimes hard to spot. Otherwise the # get things in right dimensions for calculation below

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

On 20 September 2015 at 17:39, STAR0SS wrote: > The biggest problem right now is that Prob_o is global in calc_net. You > need to pass it as an argument too. It's one of the drawback of having > everything global by default, this kind of mistakes are sometimes hard to > spot. >

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

take a look at @code_warntype calc_net(0, 0, 0, Dict{String,Float64}(), Dict{String,Float64 }()) It tells you where the compiler has problems inferring the types of the variables. Problematic in this case is b_hist::Any b_hist_col2::Any numB::Any b_hist_col2_A::Any b_hist_col2_B::Any

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

This runs in 0.3 seconds: https://github.com/KristofferC/calcnet/commit/2c252a31c34eb92842310b31d753a64727b95875 but I havent checked if the result is the same hehe. Should give you a feel how to write fast code in Julia though. Bottleneck now is all the repmats. On Sunday, September 20,

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

Uhmm... I get an error: ERROR: @code_warntype not defined Do I need to update Julia or something? I have version 0.3.11. On 20 September 2015 at 16:14, Valentin Churavy wrote: > take a look at > @code_warntype calc_net(0, 0, 0, Dict{String,Float64}(), Dict{String, >

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

Only your first post should be moderated. > On Sep 20, 2015, at 11:08 AM, Adam wrote: > > Thanks for the several comments and Daniel for the alternate versions of the > calc_net function! Viral, unfortunately I'm not a GitHub/version control user > (yet), but I've

[julia-users] Re: Julia code 5x to 30x slower than Matlab code

I managed to get another 2.5x improvement with this function: function calc_net( d::Int64, t::Int64, i::Int64, sim::Dict, param::Dict ) # name some things gamma = param["gamma"] o_vec = param["o_vec"] numO = length(o_vec) w0 = sim["w"][d, 1, i] # retrieve some history b_hist =

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

Hi Steven, I am not the OP, I am trying to help the OP with his code. Anyway, the first thing I did was replace Dict{Any,Any} by the more explicit Dict{String,Float64} but that didn't help. I did not think to try a composite type. I might try that later. It would be interesting to figure out why

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

That's very useful. I didn't know about @code_warntype. I'm going to try to replace all the Dict's with concrete types and see what happens. On 20 September 2015 at 16:14, Valentin Churavy wrote: > take a look at > @code_warntype calc_net(0, 0, 0, Dict{String,Float64}(),

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

String is not a concrete type. Consider ASCIIString or UTF8String. But if you don't need the flexibility of a Dict, a composite type will be a huge improvement. --Tim On Sunday, September 20, 2015 03:55:43 PM Daniel Carrera wrote: > Hi Steven, > > I am not the OP, I am trying to help the OP

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

This is pure speculation, but the reason you don't get the same improvement could be that 0.4 is somehow more intelligent about the use of `reshape()`. Maybe one of the reasons the program has been running faster on your computer all along is that 0.4 was getting handling the memory better to

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

I just tried it. You are right. Using slice() makes the code 9x slower for me. On 20 September 2015 at 23:14, Kristoffer Carlsson wrote: > Oh, if you are on 0.3 I am not sure if slice exist. If it does, it is > really slow. > > On Sunday, September 20, 2015 at 11:13:21 PM

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

sim is defined inside the while loop which means that it goes out of scope after the while loop end, see: http://julia.readthedocs.org/en/latest/manual/variables-and-scoping/ If you want to run a number of sims you could for example create an empty vector in the start of main and push the sims

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

Oh, if you are on 0.3 I am not sure if slice exist. If it does, it is really slow. On Sunday, September 20, 2015 at 11:13:21 PM UTC+2, Kristoffer Carlsson wrote: > > For me, your latest changes made the time go from 0.13 -> 0.11. It is > strange we have so different performances, but then

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

For me, your latest changes made the time go from 0.13 -> 0.11. It is strange we have so different performances, but then again 0.3 and 0.4 are different beasts. Adding some calls to slice and another loop gained some perf for me. Can you try:

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

Thanks Daniel! That code ran in about 0.3 seconds on my machine as well. More good progress! This puts Julia about ~5x faster than Matlab here. I tried placing "return sim" at the end of your main() function, but I still got an error saying "sim not defined." Why is that? Can I return output

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

https://github.com/timholy/ProfileView.jl is invaluable for performance tweaking. Are you on 0.4? On Sunday, September 20, 2015 at 8:26:08 PM UTC+2, Milan Bouchet-Valat wrote: > > Le dimanche 20 septembre 2015 à 20:22 +0200, Daniel Carrera a écrit : > > > > > > On 20 September 2015 at

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

Hmm... ProfileView gives me an error: ERROR: panzoom not defined in view at /home/daniel/.julia/v0.3/ProfileView/src/ProfileViewGtk.jl:32 in view at /home/daniel/.julia/v0.3/ProfileView/src/ProfileView.jl:51 in include at ./boot.jl:245 in include_from_node1 at ./loading.jl:128 while loading

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

Thanks for the comments! Daniel and Kristoffer, I ran each of your code on my machine. Daniel's ran in 2.0 seconds on my laptop (~26% of time in gc); Kristoffer's ran in about 7 seconds on my laptop (~21% of time in gc). I'm not sure why Kristoffer's took so much longer to run for me than it

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

Le dimanche 20 septembre 2015 à 20:22 +0200, Daniel Carrera a écrit : > > > On 20 September 2015 at 19:43, Kristoffer Carlsson < > kcarlsso...@gmail.com> wrote: > > Did you run the code twice to not time the JIT compiler? > > > > For me, my version runs in 0.24 and Daniels in 0.34. > > > >

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

Oh, wait, I'm an idiot. I just figured out how to use @profile... :-P On 20 September 2015 at 20:22, Daniel Carrera wrote: > Is there a good way to profile Julia code? So I have been profiling by > inserting tic() and toc() lines everywhere. On my computer @profile seems >

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

Looks like you were getting a partial installation of code that needs julia 0.4. Try Pkg.update() and it should downgrade you to an earlier version. --Tim On Sunday, September 20, 2015 08:35:28 PM Daniel Carrera wrote: > Hmm... ProfileView gives me an error: > > ERROR: panzoom not defined >

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

On 20 September 2015 at 19:43, Kristoffer Carlsson wrote: > Did you run the code twice to not time the JIT compiler? > > For me, my version runs in 0.24 and Daniels in 0.34. > > Anyway, adding this to Daniels version: >

Re: [julia-users] Re: Julia code 5x to 30x slower than Matlab code

Just another note: I suspect that the `reshape()` might be the guilty party. I am just guessing here, but I suspect that the reshape() forces a memory copy, while a regular slice just creates kind of symlink to the original data. Furthermore, I suspect that the memory copy would mean that when

[julia-users] Re: Julia code 5x to 30x slower than Matlab code

On Sunday, September 20, 2015 at 2:16:07 AM UTC+8, David Gold wrote: > > One thing I suspect is hurting you is that you're storing your parameters > in a `Dict` object. Because the parameters are all of different types, (and > because of the way you declare the `Dict`), they are stored in a

[julia-users] Re: Julia code 5x to 30x slower than Matlab code

One thing I suspect is hurting you is that you're storing your parameters in a `Dict` object. Because the parameters are all of different types, (and because of the way you declare the `Dict`), they are stored in a `Dict{Any, Any}`, which means that Julia's type inference system is unable to

[julia-users] Re: Julia code 5x to 30x slower than Matlab code

Unless you make the globals `const`, the compiler doesn't know the type of globals, so every single access to it must be "interpreted", so to speak. There are talks of adding a way to specify the type of globals, that would give them comparable speed to function arguments. On Saturday,