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I have a large set of data to process [40000x50] values.
I use Matlab on my laptop but it takes a very long time.
Recently I had an access to an HPC station with theoretically I can process parallel computing. So how can I do that? I think I can't use Matlab without a proper toolbox for "Cloud computing" so I tried Scilab and octave but things were very complicated to me.
My main objectives are:
- Processing the data and Optimizing a model.
so my questions are:
- Do I have to work on Linux to perform parallel computing? (I use windows)
- How to perform parallel computing using a free software like Scilab or Octave ( I am a little bit familiar with Scilab).
Best regards.
Scilab provides several ways for parallel computing. A good starting point is the parallel computing wiki..
A simple example using parallel_run:
function [r_min, r_med, r_max]=min_med_max(a, b, c)
r_min=min(a,b,c); r_med=median([a,b,c]); r_max=max(a,b,c);
endfunction
N=10;
A=rand(1:N);B=rand(1:N);C=rand(1:N);
[Min,Med,Max]=parallel_run(A,B,C,"min_med_max");
Note however that this does not multi process on Windows.
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This question is not about how to use matlab, but trying to find out what is happening when matab is solving a differential equation. Results are often different when using different numerical methods. i wonder which numerical method is used in matlab.
Matlab has all kinds of numerical solvers available. The basic set can be found at the bottom of this page:
https://www.mathworks.com/help/matlab/math/choose-an-ode-solver.html
If you'd like to know about a particular solver (say ode45) you can scroll to the bottom of the documentation for the given solver (for ode45 it's found here: https://www.mathworks.com/help/matlab/ref/ode45.html). For this solver the paper which explains it is linked. It may, however, be a little obtuse if you are unfamiliar with the general idea behind numerical solvers, so you might consider checking out a more pedagogical text in this area, such as the one at http://numerical.recipes/. You may also consider googling less complicated solvers like the Euler Method or the Runge-Kutta method -- both give you the flavor for how the numerical solvers work.
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I have a scalable quadratic programming problem which has around 50-1000 variables with linear constraints. I am trying to find an effective solver for this. The matlab qp solver can only solve to optimality for 100 variables for my problem. Will cplex be any better? Are there any other tools which I can use.
CPLEX will definitely be better. Everything depends on the environment you are working in. If it's not a problem for you to write a C++ program you can try COIN-OR projects, in particular Couenne http://www.coin-or.org/projects/Couenne.xml for nonlinear MIP's and IPOPT http://www.coin-or.org/projects/Ipopt.xml; for Python lovers they have Coopr, DilPy, GrumPy and other projects. You can also try GAMS https://www.gams.com/, it's great for any optimization problem. It's not a solver, more like modeling system with a large number of built in commercial and open-source solvers. It's free as long as your problem has no more than 50 variables and 50 constraints (as far as I remember).
You can try the Opti Toolbox: http://www.i2c2.aut.ac.nz/Wiki/OPTI/
It has an interface to different solvers which you can use in Matlab. (Precompiled mex files.) It can solve quadratic problems.
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I want to model production machines' failure in terms of MTBF(mean time between failure) and MTTR(mean time to repair), with exponential distribution.
Actually i am modelling a Discrete Event Simulatin (DEV/DEVS) problem. The problem is concerned with FMS(flexible manufacturing system). It involves six unreliable (likely to fail) machines which can fail during operation.
I want to know how to model unreliable machines in terms of MTBF & MTTR using exponential distribution.
Also, I want to study the effect of varying MTBF and MTTR values on the problem. e.g. Distribution used: Exponential;MTBF:400,600.....;MTTR:25,50...
Check this and the related folders, for examples of Stochastic Processes simulated under matlab, in particular, an example of a Poisson Process:
% poisson.m simulates a homogeneous Poisson process
lambda=10; % arrival rate
Tmax=3; % maximum time
T(1)=random('Exponential',1/lambda);
i=1;
while T(i) < Tmax,
T(i+1)=T(i)+random('Exponential',1/lambda);
i=i+1;
end
Y=zeros(1,i-1);
plot(T(1:(i-1)),Y,'.');
Just remember that, the Poisson Process is a chain of exponential events, as the very code suggests, Thus, for representing your machine, you just need to adapt the above code adding as many variables as machines you have...........
The rest, is part of your homework......
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i have this! RLC simple circuit
i want to analysis this circuit with different values of Resistance
but i dont know how can i draw a block diagram and simulink it with matlab, i just searched internet and found some libraries,but i didn't find anything special for my work, please if you have experience in this analysis help me and let me know how can i analysis it with MATLAB simulink
i think its very simple circuit , and if i found a way to create this in MATLAB , Matlab can analysis that easily, and i want to analysis this for different values of resistance , and i have constant L and C , for inductor and capacitor
If you're allowed and have access to it, the easiest way would be to use Simscape, which has an electrical library. See Simulink Simscape simple circuit not working for a similar question.
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Please advise on Scala environment for statistical computing and graphics similar to R or Weka.
Thanks!
Perhaps Scalalab is what you're looking for.
The scripting language is based on the Scala programming language
enhanced with high level scientific operators and with an integrated
environment that provides a Matlab-like working style. Also, all the
huge libraries of Java scientific code can be easily accessible (and
many times with a more convenient syntax). [...] A major design
priority of ScalaLab is its user-friendly interface.
See also Is there a good math/stats library for Scala?
I'd suggest Breeze : http://www.scalanlp.org/ , https://github.com/dlwh/breeze/
It has some predefined Classifiers, Learning Algorithms (SVM , Regeression...), a Plotting Library and support for matrix Multiplication.
Here you can get a quick overview: https://github.com/dlwh/breeze/wiki/Quickstart