Hello,
TLDR: Is there a way to force Matlab to consistently assign a classdef object to the same core? With a parfor loop inside another loop?

Details:
I’m working on a fairly complex/large scale project which involves a large number of classdef objects & a 3D simulation. I’m running on an HPC cluster using the Slurm scheduler.
The 3D simulation has to run in a serial triple loop (at least for now; that’s not the bottleneck).
The bottleneck is the array of objects, each of which stores its own state & calls ode15s once per iteration. These are all independent so I want to run this part in a parfor loop, and this step takes much longer than the triple loop right now.
I’m running on a small test chunk within the 3D space, with about 1200 independent objects. Ultimately this will need to scale about 100x to 150,000 objects, so I need to make this as efficient as possible.
It looks like Matlab is smartly assigning the same object to the same core for the first ~704 objects, but then after that it randomly toggles between 2 cores & a few others:
This shows ~20 loops (loop iterations going downwards), with ~1200 class objects on the X axis; the colors represent the core/task assignment on each iteration using this to create this matrix:
task = getCurrentTask();
coreID(ti, ci) = task.ID;

This plot was created assigning the objects in a parfor loop, but that didn’t help:

The basic structure of the code is this:
% pseudocode:

n_objects = 1200; % this needs to scale up to ~150,000 (so ~100x)

for i:n_objects
object_array(i) = constructor();
% also tried doing this as parfor but didn’t help
end

% … other setup code…

% Big Loop:
dt = 1; % seconds
n_timesteps = 10000;
for i = 1:n_timesteps

% unavoidable 3D triple loop update
update3D(dt);

parfor j = 1:n_objects

% each object depends on 1 scalar from the 3D matrix
object_array(i).update_ODEs(dt); % each object calls ode15s independently

end

% update 3D matrix with 1 scalar from each ODE object
end

I’ve tried adding more RAM per core, but for some reason, it still seems to break after the 704th core, which is interesting.
And doing the object initialization/constructors inside a parfor loop made the initial core assignments less consistent (top row of plot).
Anyway, thank you for your help & please let me know if you have any ideas!
I’m also curious if there’s a way to make the "Big Loop" the parfor loop, and make a "serial critical section" or something for the 3D part? Or some other hack like that?
Thank you!

ETA 7/28/25: Updated pseudocode with dt & scalar values passing between 3D simulation & ODE objectsHello,
TLDR: Is there a way to force Matlab to consistently assign a classdef object to the same core? With a parfor loop inside another loop?

Details:
I’m working on a fairly complex/large scale project which involves a large number of classdef objects & a 3D simulation. I’m running on an HPC cluster using the Slurm scheduler.
The 3D simulation has to run in a serial triple loop (at least for now; that’s not the bottleneck).
The bottleneck is the array of objects, each of which stores its own state & calls ode15s once per iteration. These are all independent so I want to run this part in a parfor loop, and this step takes much longer than the triple loop right now.
I’m running on a small test chunk within the 3D space, with about 1200 independent objects. Ultimately this will need to scale about 100x to 150,000 objects, so I need to make this as efficient as possible.
It looks like Matlab is smartly assigning the same object to the same core for the first ~704 objects, but then after that it randomly toggles between 2 cores & a few others:
This shows ~20 loops (loop iterations going downwards), with ~1200 class objects on the X axis; the colors represent the core/task assignment on each iteration using this to create this matrix:
task = getCurrentTask();
coreID(ti, ci) = task.ID;

This plot was created assigning the objects in a parfor loop, but that didn’t help:

The basic structure of the code is this:
% pseudocode:

n_objects = 1200; % this needs to scale up to ~150,000 (so ~100x)

for i:n_objects
object_array(i) = constructor();
% also tried doing this as parfor but didn’t help
end

% … other setup code…

% Big Loop:
dt = 1; % seconds
n_timesteps = 10000;
for i = 1:n_timesteps

% unavoidable 3D triple loop update
update3D(dt);

parfor j = 1:n_objects

% each object depends on 1 scalar from the 3D matrix
object_array(i).update_ODEs(dt); % each object calls ode15s independently

end

% update 3D matrix with 1 scalar from each ODE object
end

I’ve tried adding more RAM per core, but for some reason, it still seems to break after the 704th core, which is interesting.
And doing the object initialization/constructors inside a parfor loop made the initial core assignments less consistent (top row of plot).
Anyway, thank you for your help & please let me know if you have any ideas!
I’m also curious if there’s a way to make the "Big Loop" the parfor loop, and make a "serial critical section" or something for the 3D part? Or some other hack like that?
Thank you!

ETA 7/28/25: Updated pseudocode with dt & scalar values passing between 3D simulation & ODE objects Hello,
TLDR: Is there a way to force Matlab to consistently assign a classdef object to the same core? With a parfor loop inside another loop?

Details:
I’m working on a fairly complex/large scale project which involves a large number of classdef objects & a 3D simulation. I’m running on an HPC cluster using the Slurm scheduler.
The 3D simulation has to run in a serial triple loop (at least for now; that’s not the bottleneck).
The bottleneck is the array of objects, each of which stores its own state & calls ode15s once per iteration. These are all independent so I want to run this part in a parfor loop, and this step takes much longer than the triple loop right now.
I’m running on a small test chunk within the 3D space, with about 1200 independent objects. Ultimately this will need to scale about 100x to 150,000 objects, so I need to make this as efficient as possible.
It looks like Matlab is smartly assigning the same object to the same core for the first ~704 objects, but then after that it randomly toggles between 2 cores & a few others:
This shows ~20 loops (loop iterations going downwards), with ~1200 class objects on the X axis; the colors represent the core/task assignment on each iteration using this to create this matrix:
task = getCurrentTask();
coreID(ti, ci) = task.ID;

This plot was created assigning the objects in a parfor loop, but that didn’t help:

The basic structure of the code is this:
% pseudocode:

n_objects = 1200; % this needs to scale up to ~150,000 (so ~100x)

for i:n_objects
object_array(i) = constructor();
% also tried doing this as parfor but didn’t help
end

% … other setup code…

% Big Loop:
dt = 1; % seconds
n_timesteps = 10000;
for i = 1:n_timesteps

% unavoidable 3D triple loop update
update3D(dt);

parfor j = 1:n_objects

% each object depends on 1 scalar from the 3D matrix
object_array(i).update_ODEs(dt); % each object calls ode15s independently

end

% update 3D matrix with 1 scalar from each ODE object
end

I’ve tried adding more RAM per core, but for some reason, it still seems to break after the 704th core, which is interesting.
And doing the object initialization/constructors inside a parfor loop made the initial core assignments less consistent (top row of plot).
Anyway, thank you for your help & please let me know if you have any ideas!
I’m also curious if there’s a way to make the "Big Loop" the parfor loop, and make a "serial critical section" or something for the 3D part? Or some other hack like that?
Thank you!

ETA 7/28/25: Updated pseudocode with dt & scalar values passing between 3D simulation & ODE objects parallel computing, parfor, hpc, cluster, memory fragmentation MATLAB Answers — New Questions

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When using unitConvert from Celsius to Fahrenheit and vice versa I noticed it was giving me incorrect answers. It is just multiplying or dividing by 9/5ths and forgetting to add or subtract the 32. Is there a way to fix this or is this a bug.When using unitConvert from Celsius to Fahrenheit and vice versa I noticed it was giving me incorrect answers. It is just multiplying or dividing by 9/5ths and forgetting to add or subtract the 32. Is there a way to fix this or is this a bug. When using unitConvert from Celsius to Fahrenheit and vice versa I noticed it was giving me incorrect answers. It is just multiplying or dividing by 9/5ths and forgetting to add or subtract the 32. Is there a way to fix this or is this a bug. bug, symbolic MATLAB Answers — New Questions

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I want to add a column to the end of Matrix.csv (my actual data is irregular and 18000+ lines) that matches the value in the Direction column to the heading below and outputs the corresponding wDir value.
I am trying to produce something like an excel lookup function after creating headingTable through the below code.
heading = ["000", "015", "030", "045", "060", "075", "090", "105", "120", "135", "150", "165", …
"180", "195", "210", "225", "240", "255", "270", "285", "300", "315", "330", "345"];
wDir = [90 75 60 45 30 15 0 345 330 315 300 295 270 255 240 225 210 195 180 165 150 135 120 105];
count = 0;
for i =1:numel(wDir)
heading1 = heading(i);
wDir1 = wDir(i);
outData = [heading1 wDir1];
count =count + 1;
headingTable(count,:) = outData;
endI want to add a column to the end of Matrix.csv (my actual data is irregular and 18000+ lines) that matches the value in the Direction column to the heading below and outputs the corresponding wDir value.
I am trying to produce something like an excel lookup function after creating headingTable through the below code.
heading = ["000", "015", "030", "045", "060", "075", "090", "105", "120", "135", "150", "165", …
"180", "195", "210", "225", "240", "255", "270", "285", "300", "315", "330", "345"];
wDir = [90 75 60 45 30 15 0 345 330 315 300 295 270 255 240 225 210 195 180 165 150 135 120 105];
count = 0;
for i =1:numel(wDir)
heading1 = heading(i);
wDir1 = wDir(i);
outData = [heading1 wDir1];
count =count + 1;
headingTable(count,:) = outData;
end I want to add a column to the end of Matrix.csv (my actual data is irregular and 18000+ lines) that matches the value in the Direction column to the heading below and outputs the corresponding wDir value.
I am trying to produce something like an excel lookup function after creating headingTable through the below code.
heading = ["000", "015", "030", "045", "060", "075", "090", "105", "120", "135", "150", "165", …
"180", "195", "210", "225", "240", "255", "270", "285", "300", "315", "330", "345"];
wDir = [90 75 60 45 30 15 0 345 330 315 300 295 270 255 240 225 210 195 180 165 150 135 120 105];
count = 0;
for i =1:numel(wDir)
heading1 = heading(i);
wDir1 = wDir(i);
outData = [heading1 wDir1];
count =count + 1;
headingTable(count,:) = outData;
end column, lookup, matrix, table, match, matching MATLAB Answers — New Questions

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I’m currently working on the fractional Hénon map, but I’m facing difficulties in drawing the bifurcation diagrams correctly. I’m not sure how to implement the fractional order in the iteration process or which method is most suitable. I would really appreciate any guidance or examples you could provide.I’m currently working on the fractional Hénon map, but I’m facing difficulties in drawing the bifurcation diagrams correctly. I’m not sure how to implement the fractional order in the iteration process or which method is most suitable. I would really appreciate any guidance or examples you could provide. I’m currently working on the fractional Hénon map, but I’m facing difficulties in drawing the bifurcation diagrams correctly. I’m not sure how to implement the fractional order in the iteration process or which method is most suitable. I would really appreciate any guidance or examples you could provide. henon fractional map, bifurcation diagram MATLAB Answers — New Questions

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Hi friends, can I ask for your help? I am a student and am currently working on my final project. I’m stuck and don’t know who to ask for help. I’m developing a HESS supercapacitor battery system for an off-grid solar power plant. However, I’m not getting the results I want. I’m confused by the results because the current or power in the supercapacitor isn’t functioning properly, and the current or power from the battery reacts too quickly, so it doesn’t show the benefits of the supercapacitor. Does anyone know where the problem lies and how to solve it? I am willing to pay if necessary, but my funds are limited. I will do my best to make it work.Hi friends, can I ask for your help? I am a student and am currently working on my final project. I’m stuck and don’t know who to ask for help. I’m developing a HESS supercapacitor battery system for an off-grid solar power plant. However, I’m not getting the results I want. I’m confused by the results because the current or power in the supercapacitor isn’t functioning properly, and the current or power from the battery reacts too quickly, so it doesn’t show the benefits of the supercapacitor. Does anyone know where the problem lies and how to solve it? I am willing to pay if necessary, but my funds are limited. I will do my best to make it work. Hi friends, can I ask for your help? I am a student and am currently working on my final project. I’m stuck and don’t know who to ask for help. I’m developing a HESS supercapacitor battery system for an off-grid solar power plant. However, I’m not getting the results I want. I’m confused by the results because the current or power in the supercapacitor isn’t functioning properly, and the current or power from the battery reacts too quickly, so it doesn’t show the benefits of the supercapacitor. Does anyone know where the problem lies and how to solve it? I am willing to pay if necessary, but my funds are limited. I will do my best to make it work. hess, hybrid, energy, system, storage, battery_system_management, power_electronics_control, simpowersystems, pv, solar, pi, pid, supercapacitor, battery MATLAB Answers — New Questions

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Is it possible to add a secondary y axis while using the stackedplot function? I have some overlayed data in my stackedplot and I would like to add a secondary y axis for some of the individual plots. Is this possible?Is it possible to add a secondary y axis while using the stackedplot function? I have some overlayed data in my stackedplot and I would like to add a secondary y axis for some of the individual plots. Is this possible? Is it possible to add a secondary y axis while using the stackedplot function? I have some overlayed data in my stackedplot and I would like to add a secondary y axis for some of the individual plots. Is this possible? stackedplot, secondary yaxis MATLAB Answers — New Questions

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I am using MATLAB’s Classification Learner App to train multiple models (e.g., SVM, KNN, NN, etc.) on my dataset. The app displays the confusion matrix for each model individually, which is helpful.
For my research, I want to export the predicted class labels along with the true class labels for each trained model into a single .csv or .xlsx file — ideally including:
Model name
True class label
Predicted class label
How can I export these predictions for all models from Classification Learner into a table form from the classifier learner?I am using MATLAB’s Classification Learner App to train multiple models (e.g., SVM, KNN, NN, etc.) on my dataset. The app displays the confusion matrix for each model individually, which is helpful.
For my research, I want to export the predicted class labels along with the true class labels for each trained model into a single .csv or .xlsx file — ideally including:
Model name
True class label
Predicted class label
How can I export these predictions for all models from Classification Learner into a table form from the classifier learner? I am using MATLAB’s Classification Learner App to train multiple models (e.g., SVM, KNN, NN, etc.) on my dataset. The app displays the confusion matrix for each model individually, which is helpful.
For my research, I want to export the predicted class labels along with the true class labels for each trained model into a single .csv or .xlsx file — ideally including:
Model name
True class label
Predicted class label
How can I export these predictions for all models from Classification Learner into a table form from the classifier learner? confusion matrix, csv file MATLAB Answers — New Questions

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I am solving dispersion equation for water waves. I already solved it but with small h now i am using the same code but having different h and it give me incorrect evenscent modes. How i can fix my this code that it works well. Below is my code
clc;
close all;
clear all;

N = 10; % Terms number used in region I

% — 2. Dimensional geometry & environment ———————
RI = 34.5; % [m] inner / entrance radius (fully open ⇒ RI = RT)
RE = 47.5; % [m] outer hull radius (used for k0*RE axis)
d = 38.0; % [m] draft = free-surface → rim (water-column length)
h = 200; % [m] total water depth (free-surface → seabed)
b = h – d; % [m] clearance rim → seabed (= 162 m, not usually used)
g=9.81;

k0RE = linspace(5, 35, 200); % 200 points, dimension-less

I_given_wavenumber = 1;
% ————— ① pre-allocate
for j = 1:length(k0RE)
if I_given_wavenumber == 1
wk = k0RE(j)/RE; %wavenumber
omega = sqrt(g*wk*tanh(wk*h)); %wave radian frequency

fun_alpha = @(x) omega^2 + g*x*tan(x*h); %dispersion equation for evanescent modes

end
for n = 1:N
if n ==1
k(n) = -1i*wk;

else
x0_alpha = [(2*n -3)*pi/2./h, (2*n -1)*pi/2./h]; % Narrow interval
k(n) = fsolve(fun_alpha, mean(x0_alpha));
end
end

endI am solving dispersion equation for water waves. I already solved it but with small h now i am using the same code but having different h and it give me incorrect evenscent modes. How i can fix my this code that it works well. Below is my code
clc;
close all;
clear all;

N = 10; % Terms number used in region I

% — 2. Dimensional geometry & environment ———————
RI = 34.5; % [m] inner / entrance radius (fully open ⇒ RI = RT)
RE = 47.5; % [m] outer hull radius (used for k0*RE axis)
d = 38.0; % [m] draft = free-surface → rim (water-column length)
h = 200; % [m] total water depth (free-surface → seabed)
b = h – d; % [m] clearance rim → seabed (= 162 m, not usually used)
g=9.81;

k0RE = linspace(5, 35, 200); % 200 points, dimension-less

I_given_wavenumber = 1;
% ————— ① pre-allocate
for j = 1:length(k0RE)
if I_given_wavenumber == 1
wk = k0RE(j)/RE; %wavenumber
omega = sqrt(g*wk*tanh(wk*h)); %wave radian frequency

fun_alpha = @(x) omega^2 + g*x*tan(x*h); %dispersion equation for evanescent modes

end
for n = 1:N
if n ==1
k(n) = -1i*wk;

else
x0_alpha = [(2*n -3)*pi/2./h, (2*n -1)*pi/2./h]; % Narrow interval
k(n) = fsolve(fun_alpha, mean(x0_alpha));
end
end

end I am solving dispersion equation for water waves. I already solved it but with small h now i am using the same code but having different h and it give me incorrect evenscent modes. How i can fix my this code that it works well. Below is my code
clc;
close all;
clear all;

N = 10; % Terms number used in region I

% — 2. Dimensional geometry & environment ———————
RI = 34.5; % [m] inner / entrance radius (fully open ⇒ RI = RT)
RE = 47.5; % [m] outer hull radius (used for k0*RE axis)
d = 38.0; % [m] draft = free-surface → rim (water-column length)
h = 200; % [m] total water depth (free-surface → seabed)
b = h – d; % [m] clearance rim → seabed (= 162 m, not usually used)
g=9.81;

k0RE = linspace(5, 35, 200); % 200 points, dimension-less

I_given_wavenumber = 1;
% ————— ① pre-allocate
for j = 1:length(k0RE)
if I_given_wavenumber == 1
wk = k0RE(j)/RE; %wavenumber
omega = sqrt(g*wk*tanh(wk*h)); %wave radian frequency

fun_alpha = @(x) omega^2 + g*x*tan(x*h); %dispersion equation for evanescent modes

end
for n = 1:N
if n ==1
k(n) = -1i*wk;

else
x0_alpha = [(2*n -3)*pi/2./h, (2*n -1)*pi/2./h]; % Narrow interval
k(n) = fsolve(fun_alpha, mean(x0_alpha));
end
end

end evenscent modes, dispersion equation, water waves MATLAB Answers — New Questions

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