# Dynare parallel

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## Description

In this quick tutorial, I will cover the necessary steps to run dynare parallel for (i) Windows, (ii) macOS, and (iii) Ubuntu Linux (which should also work on other Linux distributions). After some general remarks and establishing the example model, where we estimate a small model using the Random-Walk Metropolis-Hastings with 4 chains computed in parallel, I provide the required steps for each operating system. There are also videos below you might find useful to follow.

## General remarks and example model

Let’s consider the following example mod file called mymodel.mod:

var YGR INFL INT y c r p g z;
varobs YGR INFL INT;
varexo epsr epsg epsz;

parameters TAU KAPPA PSI1 PSI2 RHOR RHOG RHOZ RA PA GAMQ;

TAU     = 2.00; PSI1    = 1.50; RHOR    = 0.60;
KAPPA   = 0.15; PSI2    = 1.00; RHOG    = 0.95;
RA      = 0.40; GAMQ    = 0.50; RHOZ    = 0.65;
PA      = 4.00;

model;
#dy = y - y(-1);
#BET = 1/(1+RA/400);
y = y(+1) + g - g(+1) -1/TAU*(r - p(+1) - z(+1));
p = BET*p(+1) + KAPPA*(y - g);
c = y - g;
r = RHOR*r(-1) + (1-RHOR)*PSI1*p + (1-RHOR)*PSI2*(dy + z) + epsr/100;
g = RHOG*g(-1) + epsg/100;
z = RHOZ*z(-1) + epsz/100;
YGR = GAMQ + 100*(y - y(-1) + z);
INFL = PA + 400*p;
INT = PA + RA + 4*GAMQ + 400*r;
end;

z = 0; p = 0; g = 0; r = 0; c = 0; y = 0;
YGR = GAMQ; INFL = PA; INT = PA + RA + 4*GAMQ;
end;

shocks;
var epsr = 0.20^2;
var epsg = 0.80^2;
var epsz = 0.45^2;
end;

estimated_params;
TAU,             2.00,          1e-5,        10,          gamma_pdf,     2.00,       0.50;
KAPPA,           0.15,          1e-5,        10,          gamma_pdf,     0.20,       0.10;
PSI1,            1.50,          1e-5,        10,          gamma_pdf,     1.50,       0.25;
PSI2,            1.00,          1e-5,        10,          gamma_pdf,     0.50,       0.25;
RHOR,            0.60,          1e-5,        0.99999,     beta_pdf,      0.50,       0.20;
RHOG,            0.95,          1e-5,        0.99999,     beta_pdf,      0.80,       0.10;
RHOZ,            0.64,          1e-5,        0.99999,     beta_pdf,      0.66,       0.15;
RA,              0.40,          1e-5,        10,          gamma_pdf,     0.50,       0.50;
PA,              4.00,          1e-5,        20,          gamma_pdf,     7.00,       2.00;
GAMQ,            0.50,          -5,          5,           normal_pdf,    0.40,       0.20;
stderr epsr,     0.20,          1e-8,        5,           inv_gamma_pdf, 0.50,       0.26;
stderr epsg,     0.80,          1e-8,        5,           inv_gamma_pdf, 1.25,       0.65;
stderr epsz,     0.45,          1e-8,        5,           inv_gamma_pdf, 0.63,       0.33;
end;

stoch_simul(order=1,IRF=0,periods=10000);
save('simdat.mat', options_.varobs{:} );

estimation(datafile='simdat.mat',
first_obs                 = 5001,
nobs                      = 100,
mode_compute              = 4,
mcmc_jumping_covariance   = hessian,
mh_replic                 = 2001,
mh_nblocks                = 4,
mh_jscale                 = 0.4,
posterior_sampling_method = 'random_walk_metropolis_hastings',
posterior_sampler_options = ('proposal_distribution', 'rand_multivariate_student',
'student_degrees_of_freedom', 3)
);


Let’s run this mod file:

dynare mymodel


Note that by default all tasks are single threaded in Dynare (except some MEX files), i.e. they are run on a single core. Let’s assume, however, that our machine has 4 CPUs, then the estimation command will run each chain sequentially and on core only; this is inefficient as the other 3 cores have nothing to do. Dynare has the ability to run the following tasks in parallel:

• the posterior sampling algorithms when using multiple chains
• the Metropolis-Hastings diagnostics
• the posterior IRFs
• the prior and posterior statistics
• some plotting routines

The parallelization is done by running several MATLAB or Octave processes in the background, either on local or on remote machines.1 Communication between master and slave processes are done through SMB on Windows and SSH on UNIX. Input and output data, and also some short status messages, are exchanged through network filesystems. Currently the system works only with homogenous grids: only Windows or only Unix machines. Running Dynare in parallel is actually quite easy:

dynare mymodel parallel


However, we need to set up a configuration file first, which is a bit different for each operating system. The manual has a dedicated section on how to set up a configuration file for Dynare. We will cover a basic use case, i.e. running stuff in parallel on a local notebook or desktop computer or server, i.e. on localhost.

## Windows





### Step 1: PsTools

First you need to download PsTools and extract it to an arbitrary folder, e.g. C:\dynare\PSTools. Then you have to add this folder to your PATH. To this end, use this key combo: WIN+PAUSE which will open up a System Settings panel with basic information about your computer. On the left choose Advanced system settings, then Environmental Variables. Click on Path in the User variables section and click on Edit. Hit New and provide the path to PSTools, e.g. C:\dynare\PSTools . Click OK and close all windows. Now open a command prompt and type psexec and psinfo which should give you a license agreement window which you should agree to.

### Step 2: Configuration file

Create a new file with a text editor or MATLAB’s script editor and call it, for example, myconf.

In this file, we need to specify some settings to identify our machine and number of cores to use. Here is an example file:

[cluster]
Name = Local
Members = n1

[node]
Name = n1
ComputerName = localhost
CPUnbr = 4


As we have only one machine, our cluster contains only one member n1. For each member, we need to specify options in the node section. The name must correspond to the Members declared above. We don’t use a remote machine, so we select localhost . The most important setting is CPUnbr which corresponds to the number of cores you have. You can also (optionally) set the NumberOfThreadsPerJob to a number. For instance, if you have 8 cores and set CPUnbr = 8 and NumberOfThreadsPerJob=2, Dynare parallel will run 8/2=4 chains in parallel.

### Step 3: Running dynare parallel

Now we should first test our configuration file by calling:

dynare mymodel parallel_test confile=myconf


If everything is okay, we can actually do the parallel estimation by calling:

dynare mymodel parallel confile=myconf


Another hint: If you always use the same configuration file, you can copy your configruation myconf into C:\Users\wmutschl\AppData\Roaming and rename it to dynare.ini. Then you can omit the conffile argument to the call above. Note, however, that the conffile option is more flexible.

## MacOS





### Step 1: Configuration file

Create a new file with a text editor or MATLAB’s script editor and call it, for example, myconf.

In this file, we need to specify some settings to identify our machine and number of cores to use. Here is an example file:

[cluster]
Name = Local
Members = n1

[node]
Name = n1
ComputerName = localhost
CPUnbr = 4
MatlabOctavePath=/Applications/MATLAB_R2020a.app/bin/matlab


As we have only one machine, our cluster contains only one member n1. For each member, we need to specify options in the node section. The name must correspond to the Members declared above. We don’t use a remote machine, so we select localhost . The most important setting is CPUnbr which corresponds to the number of cores you have. You can also (optionally) set the NumberOfThreadsPerJob to a number. For instance, if you have 8 cores and set CPUnbr = 8 and NumberOfThreadsPerJob=2, Dynare parallel will run 8/2=4 chains in parallel. Note that for MacOS it is important to set the MatlabOctavePath pointing to your binary of either MATLAB or Octave.

### Step 2: Running dynare parallel

Now we should first test our configuration file by calling:

dynare mymodel parallel_test confile=myconf


If everything is okay, we can actually do the parallel estimation by calling:

dynare mymodel parallel confile=myconf


Another hint: If you always use the same configuration file, you can copy your myconf file to /Users/wmutschl and rename it to .dynare (note that this becomes a hidden file). Then you can omit the conffile argument to the call above. Note, however, that the conffile option is more flexible.

## Linux





### Step 1: Configuration file

Create a new file with a text editor or MATLAB’s script editor and call it, for example, myconf.

In this file, we need to specify some settings to identify our machine and number of cores to use. Here is an example file:

[cluster]
Name = Local
Members = n1

[node]
Name = n1
ComputerName = localhost
CPUnbr = 4


As we have only one machine, our cluster contains only one member n1. For each member, we need to specify options in the node section. The name must correspond to the Members declared above. We don’t use a remote machine, so we select localhost . The most important setting is CPUnbr which corresponds to the number of cores you have. You can also (optionally) set the NumberOfThreadsPerJob to a number. For instance, on our university cluster (where each node has 72 CPUs) I usually run 72/9=8 MCMC chains in parallel by using the following configuration file:

[cluster]
Name = Local
Members = n1

[node]
Name = n1
ComputerName = localhost
CPUnbr = 72


### Step 2: Running dynare parallel

Now we should first test our configuration file by calling:

dynare mymodel parallel_test confile=myconf


If everything is okay, we can actually do the parallel estimation by calling:

dynare mymodel parallel confile=myconf


Another hint: If you always use the same configuration file, you can copy your myconf file to /home/wmutschl and rename it to .dynare (note that this becomes a hidden file). Then you can omit the conffile argument to the call above. Note, however, that the conffile option is more general and flexible.

1. In Dynare 4.8 we plan to revise the parallel toolbox and I will update this guide accordingly. ↩︎