Call to inv() function seems to have (undesired) impact on Thread pool or maxNumCompThreads()
I tried to parallelize parts of my code via parpool("Threads"). I also use maxNumCompThreads to limit the maximum CPU utilization. I use a parfor loop which works as expected, meaning that the defined number of cores corresponds to the total cpu utilization shown in the windows taks manager (more or less).
However, if a call to the inv() function appears somewhere in the code before the thread pool is started, then the cpu utilization of the thread pool is unexpectedly higher, although the number of cores and also maxNumCompThreads is not changed. This happens reproducible, until matlab is restarted (and inv() is not called).
To obtain the unexpected behavior the input to inv() must exceed a certain size: inv(rand(10)) –> nothing happens, but inv(rand(1000)) –> CPU utilization of the following parfor loop is unexpectedly high.
A simple script to reproduce the described behavior (in matlab2023b):
maxNumCompThreads(12);
nCores = 12;
%% random parallel code
fprintf("Before inv function call:n");
pp = parpool("Threads", nCores);
for j = 1:3
tic;
parfor (i = 1:100)
A = rand(1000) / rand(1000);
end
toc
pause(2);
end
delete(pp);
%% matrix inverse
Minv = inv(rand(5000));
pause(5);
%% same random parallel code as before –> CPU Utilization goes up to 100%
fprintf("nnAfter inv function call:n");
pp = parpool("Threads", nCores);
for j = 1:3
tic;
parfor (i = 1:100)
A = rand(1000) / rand(1000);
end
toc
pause(2);
end
delete(pp);
On a 56-core machine, the first parallel block runs with < 20% CPU utilization, while the second block has ~50%.
I get the following output:
Before inv function call:
Starting parallel pool (parpool) using the ‘Threads’ profile …
Connected to parallel pool with 12 workers.
Elapsed time is 5.852217 seconds.
Elapsed time is 2.475874 seconds.
Elapsed time is 2.447292 seconds.
Parallel pool using the ‘Threads’ profile is shutting down.
After inv function call:
Starting parallel pool (parpool) using the ‘Threads’ profile …
Connected to parallel pool with 12 workers.
Elapsed time is 23.414892 seconds.
Elapsed time is 24.350276 seconds.
Elapsed time is 23.297744 seconds.
Parallel pool using the ‘Threads’ profile is shutting down.
The increased core utilization for Thread pools stays present until matlab is closed an restarted. With parpool("Processes") I did not observe this behavior.
Am I missing anything here?I tried to parallelize parts of my code via parpool("Threads"). I also use maxNumCompThreads to limit the maximum CPU utilization. I use a parfor loop which works as expected, meaning that the defined number of cores corresponds to the total cpu utilization shown in the windows taks manager (more or less).
However, if a call to the inv() function appears somewhere in the code before the thread pool is started, then the cpu utilization of the thread pool is unexpectedly higher, although the number of cores and also maxNumCompThreads is not changed. This happens reproducible, until matlab is restarted (and inv() is not called).
To obtain the unexpected behavior the input to inv() must exceed a certain size: inv(rand(10)) –> nothing happens, but inv(rand(1000)) –> CPU utilization of the following parfor loop is unexpectedly high.
A simple script to reproduce the described behavior (in matlab2023b):
maxNumCompThreads(12);
nCores = 12;
%% random parallel code
fprintf("Before inv function call:n");
pp = parpool("Threads", nCores);
for j = 1:3
tic;
parfor (i = 1:100)
A = rand(1000) / rand(1000);
end
toc
pause(2);
end
delete(pp);
%% matrix inverse
Minv = inv(rand(5000));
pause(5);
%% same random parallel code as before –> CPU Utilization goes up to 100%
fprintf("nnAfter inv function call:n");
pp = parpool("Threads", nCores);
for j = 1:3
tic;
parfor (i = 1:100)
A = rand(1000) / rand(1000);
end
toc
pause(2);
end
delete(pp);
On a 56-core machine, the first parallel block runs with < 20% CPU utilization, while the second block has ~50%.
I get the following output:
Before inv function call:
Starting parallel pool (parpool) using the ‘Threads’ profile …
Connected to parallel pool with 12 workers.
Elapsed time is 5.852217 seconds.
Elapsed time is 2.475874 seconds.
Elapsed time is 2.447292 seconds.
Parallel pool using the ‘Threads’ profile is shutting down.
After inv function call:
Starting parallel pool (parpool) using the ‘Threads’ profile …
Connected to parallel pool with 12 workers.
Elapsed time is 23.414892 seconds.
Elapsed time is 24.350276 seconds.
Elapsed time is 23.297744 seconds.
Parallel pool using the ‘Threads’ profile is shutting down.
The increased core utilization for Thread pools stays present until matlab is closed an restarted. With parpool("Processes") I did not observe this behavior.
Am I missing anything here? I tried to parallelize parts of my code via parpool("Threads"). I also use maxNumCompThreads to limit the maximum CPU utilization. I use a parfor loop which works as expected, meaning that the defined number of cores corresponds to the total cpu utilization shown in the windows taks manager (more or less).
However, if a call to the inv() function appears somewhere in the code before the thread pool is started, then the cpu utilization of the thread pool is unexpectedly higher, although the number of cores and also maxNumCompThreads is not changed. This happens reproducible, until matlab is restarted (and inv() is not called).
To obtain the unexpected behavior the input to inv() must exceed a certain size: inv(rand(10)) –> nothing happens, but inv(rand(1000)) –> CPU utilization of the following parfor loop is unexpectedly high.
A simple script to reproduce the described behavior (in matlab2023b):
maxNumCompThreads(12);
nCores = 12;
%% random parallel code
fprintf("Before inv function call:n");
pp = parpool("Threads", nCores);
for j = 1:3
tic;
parfor (i = 1:100)
A = rand(1000) / rand(1000);
end
toc
pause(2);
end
delete(pp);
%% matrix inverse
Minv = inv(rand(5000));
pause(5);
%% same random parallel code as before –> CPU Utilization goes up to 100%
fprintf("nnAfter inv function call:n");
pp = parpool("Threads", nCores);
for j = 1:3
tic;
parfor (i = 1:100)
A = rand(1000) / rand(1000);
end
toc
pause(2);
end
delete(pp);
On a 56-core machine, the first parallel block runs with < 20% CPU utilization, while the second block has ~50%.
I get the following output:
Before inv function call:
Starting parallel pool (parpool) using the ‘Threads’ profile …
Connected to parallel pool with 12 workers.
Elapsed time is 5.852217 seconds.
Elapsed time is 2.475874 seconds.
Elapsed time is 2.447292 seconds.
Parallel pool using the ‘Threads’ profile is shutting down.
After inv function call:
Starting parallel pool (parpool) using the ‘Threads’ profile …
Connected to parallel pool with 12 workers.
Elapsed time is 23.414892 seconds.
Elapsed time is 24.350276 seconds.
Elapsed time is 23.297744 seconds.
Parallel pool using the ‘Threads’ profile is shutting down.
The increased core utilization for Thread pools stays present until matlab is closed an restarted. With parpool("Processes") I did not observe this behavior.
Am I missing anything here? maxnumcompthreads, parpool, threads, inv MATLAB Answers — New Questions
