matlab 2016a (linux) memory leak
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Dear community,
several months ago I installed ver. 2016a on out Linux (Ubuntu) Workstation. With the time I saw the this version continuously slows down while using it and become unusable. Matlab restart helps.
Tracing down the issue, I saw the this Matlab version uses more and more memory with the time (~100GB ram in less than 10 mins while analyzing the data, even after clear all).
This is a very strong hint to the memory leak, as in addition to that ver. 2014b does not have this problem.
I did not track down where exactly this happens, but my scripts use a lot of binary and text file r/o operations, such as fopen, fwrite etc. This may be the cause.
So far, using ver. 2014b helps.
Did anybody else experience that and aware about patches?
1 Comment
Answers (4)
Vassilis Lemonidis
on 25 Apr 2021
Do we have any news on that issue? It seems still to affect R2020b parallel processing on Linux, clear all does not release workers memory and Matlab needs to be manually closed and restarted after every code execution to forcibly release it. If you believe that it is a problem with the code I am using, could you please direct me to a method that I could add to the classes I have constructed and I am using, which could handle the garbage collection process? Also, is there a tool to identify weak pointers that clear all cannot handle well?
3 Comments
Vassilis Lemonidis
on 25 Apr 2021
Unfortunately I am bound to use a more updated version of Matlab, as I have mat-files from newer versions that will lose information if reverted to an older one, while I am also using toolboxes that were previously aso not available... Thank you whatsoever for the suggestion, it is a bit annoying that nothing has been done to fix this behavior, after so many versions and years having passed....
Haiying Tang
on 7 Nov 2017
Edited: Haiying Tang
on 7 Nov 2017
We got this error too!
Actually, It occurred both in R2015b and R2016b for Linux, but R2014b is OK!
We tested the same codes in R2014b, R2015b and R2016b on CentOS 7. Our Matlab code(exported to a Java package by MCC) uses the Parallel Computing Toolbox and runs under the MCR with 16-core CPU and 16G RAM servers. In R2014b, each worker keeps about 500M and runs normally, while in R2015b and R2016b, it increase the memory until the worker exit(killed by the OS) after running about 24 hours.
Because of this memory issue, we have to keep using the R2014b at present!
Hope someone can help us and thanks a lot!
(Posted by my technical workmate: Pingmin Fenlly Liu)
3 Comments
Steven Lord
on 7 Nov 2017
Please contact Technical Support using the Contact Us link in the upper-right corner of this page. Provide them a code segment or workflow with which you can reproduce this memory increase and work with them to determine if this is actually a bug and if so how to resolve it.
mikhailo
on 7 Nov 2017
Edited: mikhailo
on 7 Nov 2017
7 Comments
Steven Lord
on 9 Nov 2017
I searched the Bug Reports for any bugs that mention "parfor" and existed in release R2016a, but none seemed to deal with memory leaking.
As I stated above, I strongly recommend that if possible you send a small sample of the code that shows this behavior to Technical Support using the Contact Us link in the upper-right corner of this page so they (and the development team) can investigate.
Even if you can't isolate the problem down to a particular segment of code, you might want to contact them and ask what steps they recommend to use to investigate the problem. They may be able to help you narrow down the location of the problem to the point where they can pinpoint what's going on.
Zhuo Chen
on 9 Nov 2017
Hi,
I understand that your MATLAB is running slowly. I have a few things for you to try regarding this issue.
First, please navigate to the Java Heap Memory preferences and increase the allocated value to 2048MB. Then restart MATLAB and see if the lag occurs on start-up and throughout your work.
Secondly, please disable the source control integration for MATLAB. You can find this at Preferences > MATLAB > General > Source Control and select "None". Restart MATLAB and then see if there is a change in the performance.
I strongly recommend that if possible you post a small sample of the code that shows this behavior here.
2 Comments
Pingmin Fenlly Liu
on 10 Nov 2017
It's not the slow response of Matlab, but the memory leak (almost) in MCR. Thank you all the same.
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