[julia-users] Re: Questions on parallelizing code - or how to deal with objects (and not just gathering data) in parallel.

MPI.jl has a montecarlo.jl function which could possibly be used. A simple example which shows the ideas is https://github.com/JuliaParallel/MPI.jl/blob/master/examples/07-pi-montecarlo.jl montecarlo.jl automatically collects results. The part about updating the state and broadcasting the

[julia-users] Re: AutoGrad port for Julia

I've cloned it and tried it out with RC3. The mnist example runs fine. I'm looking forward to exploring it in more detail. Thanks! On Friday, August 26, 2016 at 8:51:30 AM UTC+2, Deniz Yuret wrote: > > Announcing AutoGrad.jl : an > automatic

[julia-users] Re: why's my julia code running slower than matlab, despite performance tips

I see that c is a constant array of Ints, and its elements multiply ux, uy and uz in a loop, where ux, uy and uz are arrays of floats, so there's a type stability problem. On Sunday, May 8, 2016 at 9:18:09 AM UTC+2, feza wrote: > > https://gist.github.com/musmo/27436a340b41c01d51d557a655276783

[julia-users] Re: Your experiences with Julia's parallel computing

> > >- What is the main reason that you started using Julia? > > Free, fast, works on all popular operating systems, so good for teaching and portability of research > >- Have you used Julia’s parallel computing aspects? > > Yes, but I mostly use the MPI.jl package. > >- What did

[julia-users] Re: Julia and Octave communication using MPI?

I have given this a shot. Using the two files testOctaveJulia.m and testOctaveJulia.jl testOctaveJulia.m: if not(MPI_Initialized) MPI_Init; end CW = MPI_Comm_Load("NEWORLD"); myrank = MPI_Comm_rank(CW); commsize = MPI_Comm_size(CW); sleep(myrank*0.5); printf("I am Octave rank %d\n", myrank);

[julia-users] Julia and Octave communication using MPI?

I use MPI with both Julia (using MPI.jl) and Octave (using the MPI package for Octave). For both Julia and Octave, the packages are wrapping (in my case) Open MPI functions. I believe that it should be possible for Julia and Octave to send information back and forth via MPI. Before trying this

[julia-users] Re: deep learning for regression?

To report back, my experience with Mocha.jl has been very good. The following is an example of how one can do regression with Mocha. This assumes that there are two data files "train.dat" and "test.dat", which are plain ascii files, space delimited, variables in columns. The outputs are in

[julia-users] Re: deep learning for regression?

Thanks everyone for the comments and pointers to code. I have coded up a simple example, fitting y=sin(x) + error, and the results very good, enough so that I'll certainly be investigating further with larger scale problems. I may try to use one of the existing packages, but it may be

[julia-users] deep learning for regression?

I'm interested in using neural networks (deep learning) for multivariate multiple regression, with multiple real valued inputs and multiple real valued outputs. At the moment, the mocha.jl package looks very promising, but the examples seem to be all for classification problems. Does anyone

[julia-users] Re: deep learning for regression?

Thanks, that's pretty much my understanding. Scaling the inputs seems to be important, too, from what I read. I'm also interested in a framework that will trim off redundant inputs. I have run the mocha tutorial examples, and it looks very promising because the structure is clear, and there

[julia-users] Re: Running multiple scripts in parallel Julia sessions

It would be easy to do this using the MPI.jl package. That's what I would do, but only because I'm familiar with how it works. The native parallel methods of Julia may work just as well, though. On Saturday, January 23, 2016 at 5:08:11 AM UTC+1, Ritchie Lee wrote: > > Let's say I have 10 julia

[julia-users] Code for simulated annealing minimization over a box subset of R^d

The following is code for simulated annealing minimization. The parameter space is a box constrained subset of R^d. This code follows the article Goffe, William L. (1996) "SIMANN: A Global Optimization Algorithm using Simulated Annealing " Studies in Nonlinear Dynamics & Econometrics, Oct96,

[julia-users] Re: help speeding up nonparametric regression?

I did profiling, and ProfileView.jl worked fine, and is definitely pretty slick. There were no surprises, though, the sections with the @time-ings are the ones that are costly. On Thursday, December 17, 2015 at 6:27:11 PM UTC+1, michae...@gmail.com wrote: > > I tried using the profiler with

[julia-users] Re: help speeding up nonparametric regression?

No, I haven't used the profiler. However, I already know that most time is spend in the two parts that are @time-ed. If you put a @time in front of main() you get something like (I'm using Julia 4.3-pre6 on Debian): julia> include("testnpreg.jl") 1.228517 seconds (34.96 k allocations: 764.159

[julia-users] Re: help speeding up nonparametric regression?

I tried using the profiler with another problem a few months ago, and ProfileView was not working for me then. I will give it another try. However, the parts of the code that impact the timing are pretty narrowly identified already. I have read the performance guide pretty carefully, and I

[julia-users] help speeding up nonparametric regression?

I am working on some code for nonparametric regression using local constant, local linear, and local quadratic fits. I would like to speed up the function npreg, which is contained in the attached code. This function gets the fit by weighted least square regression. I suspect that there may be

[julia-users] Re: help speeding up nonparametric regression?

Here's the code in that attachment: using Winston using Distributions # nonparametric regression, using pre-generated weights # can be local constant, local linear, or local quadratic # # y is n X p # x is n X dimx # xeval is neval X dimx # weights is n X neval (different weights for each eval.

[julia-users] convert Array{Float,1} to Array{Float,2)?

I have a function that expects a Matrix argument, but for the case I'm working on, the natural way to construct the argument gives a vector. So, suppose I have a vector, e.g., a=rand(10). What is the best way to convert this to a 10X1 array? I can do it using a loop, but I thought there might

Re: [julia-users] convert Array{Float,1} to Array{Float,2)?

Thanks. I knew there had to be an easy way. On Tuesday, October 27, 2015 at 12:59:43 PM UTC+1, Yichao Yu wrote: > > On Tue, Oct 27, 2015 at 5:47 AM, > wrote: > > I have a function that expects a Matrix argument, but for the case I'm > > working on, the natural way to

[julia-users] Code for approximate Bayesian computing (ABC) and related estimators

Code for ABC estimation is at https://github.com/mcreel/ABCAuction The ABC code is in the directory AuctionSBIL. The file AIS.jl is a set of functions for generic ABC estimation. The file Auction.jl contains functions for a specific model, a structural auction model. The file AuctionMC.jl

[julia-users] Monte Carlo examples using the MPI package

https://github.com/mcreel/JuliaMPIMonteCarlo has code for doing Monte Carlo using the MPI package (https://github.com/JuliaParallel/MPI.jl). A note addressed to primarily to economists gives some discussion. The intention is to get beginners started, but there is also a more complex example.

[julia-users] Re: Why does my Julia code run so slow?

What's the type of c.outputs? In train_one it seems to be Int64, in prdict! it seems to be Float64. On Thursday, February 19, 2015 at 3:51:20 PM UTC+1, Zhixuan Yang wrote: Hello everyone, Recently I'm working on my first Julia project, a word embedding training program similar to Google's